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	<!DOCTYPE html>
	<html>
	<head><meta charset="utf-8" />
	<title>H2O_automl_model</title><script src="https://cdnjs.cloudflare.com/ajax/libs/require.js/2.1.10/require.min.js"></script>
	<script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/2.0.3/jquery.min.js"></script>

	<style type="text/css">
	/*!
	*
	* Twitter Bootstrap
	*
	*/
	/*!
	* Bootstrap v3.3.7 (http://getbootstrap.com)
	* Copyright 2011-2016 Twitter, Inc.
	* Licensed under MIT (https://github.com/twbs/bootstrap/blob/master/LICENSE)
	*/
	/! normalize.css v3.0.3 \| MIT License \| github.com/necolas/normalize.css /
	html {
	font-family: sans-serif;
	-ms-text-size-adjust: 100%;
	-webkit-text-size-adjust: 100%;
	}
	body {
	margin: 0;
	}
	article,
	aside,
	details,
	figcaption,
	figure,
	footer,
	header,
	hgroup,
	main,
	menu,
	nav,
	section,
	summary {
	display: block;
	}
	audio,
	canvas,
	progress,
	video {
	display: inline-block;
	vertical-align: baseline;
	}
	audio:not([controls]) {
	display: none;
	height: 0;
	}
	[hidden],
	template {
	display: none;
	}
	a {
	background-color: transparent;
	}
	a:active,
	a:hover {
	outline: 0;
	}
	abbr[title] {
	border-bottom: 1px dotted;
	}
	b,
	strong {
	font-weight: bold;
	}
	dfn {
	font-style: italic;
	}
	h1 {
	font-size: 2em;
	margin: 0.67em 0;
	}
	mark {
	background: #ff0;
	color: #000;
	}
	small {
	font-size: 80%;
	}
	sub,
	sup {
	font-size: 75%;
	line-height: 0;
	position: relative;
	vertical-align: baseline;
	}
	sup {
	top: -0.5em;
	}
	sub {
	bottom: -0.25em;
	}
	img {
	border: 0;
	}
	svg:not(:root) {
	overflow: hidden;
	}
	figure {
	margin: 1em 40px;
	}
	hr {
	box-sizing: content-box;
	height: 0;
	}
	pre {
	overflow: auto;
	}
	code,
	kbd,
	pre,
	samp {
	font-family: monospace, monospace;
	font-size: 1em;
	}
	button,
	input,
	optgroup,
	select,
	textarea {
	color: inherit;
	font: inherit;
	margin: 0;
	}
	button {
	overflow: visible;
	}
	button,
	select {
	text-transform: none;
	}
	button,
	html input[type="button"],
	input[type="reset"],
	input[type="submit"] {
	-webkit-appearance: button;
	cursor: pointer;
	}
	button[disabled],
	html input[disabled] {
	cursor: default;
	}
	button::-moz-focus-inner,
	input::-moz-focus-inner {
	border: 0;
	padding: 0;
	}
	input {
	line-height: normal;
	}
	input[type="checkbox"],
	input[type="radio"] {
	box-sizing: border-box;
	padding: 0;
	}
	input[type="number"]::-webkit-inner-spin-button,
	input[type="number"]::-webkit-outer-spin-button {
	height: auto;
	}
	input[type="search"] {
	-webkit-appearance: textfield;
	box-sizing: content-box;
	}
	input[type="search"]::-webkit-search-cancel-button,
	input[type="search"]::-webkit-search-decoration {
	-webkit-appearance: none;
	}
	fieldset {
	border: 1px solid #c0c0c0;
	margin: 0 2px;
	padding: 0.35em 0.625em 0.75em;
	}
	legend {
	border: 0;
	padding: 0;
	}
	textarea {
	overflow: auto;
	}
	optgroup {
	font-weight: bold;
	}
	table {
	border-collapse: collapse;
	border-spacing: 0;
	}
	td,
	th {
	padding: 0;
	}
	/! Source: https://github.com/h5bp/html5-boilerplate/blob/master/src/css/main.css /
	@media print {
	*,
	*:before,
	*:after {
	background: transparent !important;
	color: #000 !important;
	box-shadow: none !important;
	text-shadow: none !important;
	}
	a,
	a:visited {
	text-decoration: underline;
	}
	a[href]:after {
	content: " (" attr(href) ")";
	}
	abbr[title]:after {
	content: " (" attr(title) ")";
	}
	a[href^="#"]:after,
	a[href^="javascript:"]:after {
	content: "";
	}
	pre,
	blockquote {
	border: 1px solid #999;
	page-break-inside: avoid;
	}
	thead {
	display: table-header-group;
	}
	tr,
	img {
	page-break-inside: avoid;
	}
	img {
	max-width: 100% !important;
	}
	p,
	h2,
	h3 {
	orphans: 3;
	widows: 3;
	}
	h2,
	h3 {
	page-break-after: avoid;
	}
	.navbar {
	display: none;
	}
	.btn > .caret,
	.dropup > .btn > .caret {
	border-top-color: #000 !important;
	}
	.label {
	border: 1px solid #000;
	}
	.table {
	border-collapse: collapse !important;
	}
	.table td,
	.table th {
	background-color: #fff !important;
	}
	.table-bordered th,
	.table-bordered td {
	border: 1px solid #ddd !important;
	}
	}
	@font-face {
	font-family: 'Glyphicons Halflings';
	src: url('../components/bootstrap/fonts/glyphicons-halflings-regular.eot');
	src: url('../components/bootstrap/fonts/glyphicons-halflings-regular.eot?#iefix') format('embedded-opentype'), url('../components/bootstrap/fonts/glyphicons-halflings-regular.woff2') format('woff2'), url('../components/bootstrap/fonts/glyphicons-halflings-regular.woff') format('woff'), url('../components/bootstrap/fonts/glyphicons-halflings-regular.ttf') format('truetype'), url('../components/bootstrap/fonts/glyphicons-halflings-regular.svg#glyphicons_halflingsregular') format('svg');
	}
	.glyphicon {
	position: relative;
	top: 1px;
	display: inline-block;
	font-family: 'Glyphicons Halflings';
	font-style: normal;
	font-weight: normal;
	line-height: 1;
	-webkit-font-smoothing: antialiased;
	-moz-osx-font-smoothing: grayscale;
	}
	.glyphicon-asterisk:before {
	content: "\002a";
	}
	.glyphicon-plus:before {
	content: "\002b";
	}
	.glyphicon-euro:before,
	.glyphicon-eur:before {
	content: "\20ac";
	}
	.glyphicon-minus:before {
	content: "\2212";
	}
	.glyphicon-cloud:before {
	content: "\2601";
	}
	.glyphicon-envelope:before {
	content: "\2709";
	}
	.glyphicon-pencil:before {
	content: "\270f";
	}
	.glyphicon-glass:before {
	content: "\e001";
	}
	.glyphicon-music:before {
	content: "\e002";
	}
	.glyphicon-search:before {
	content: "\e003";
	}
	.glyphicon-heart:before {
	content: "\e005";
	}
	.glyphicon-star:before {
	content: "\e006";
	}
	.glyphicon-star-empty:before {
	content: "\e007";
	}
	.glyphicon-user:before {
	content: "\e008";
	}
	.glyphicon-film:before {
	content: "\e009";
	}
	.glyphicon-th-large:before {
	content: "\e010";
	}
	.glyphicon-th:before {
	content: "\e011";
	}
	.glyphicon-th-list:before {
	content: "\e012";
	}
	.glyphicon-ok:before {
	content: "\e013";
	}
	.glyphicon-remove:before {
	content: "\e014";
	}
	.glyphicon-zoom-in:before {
	content: "\e015";
	}
	.glyphicon-zoom-out:before {
	content: "\e016";
	}
	.glyphicon-off:before {
	content: "\e017";
	}
	.glyphicon-signal:before {
	content: "\e018";
	}
	.glyphicon-cog:before {
	content: "\e019";
	}
	.glyphicon-trash:before {
	content: "\e020";
	}
	.glyphicon-home:before {
	content: "\e021";
	}
	.glyphicon-file:before {
	content: "\e022";
	}
	.glyphicon-time:before {
	content: "\e023";
	}
	.glyphicon-road:before {
	content: "\e024";
	}
	.glyphicon-download-alt:before {
	content: "\e025";
	}
	.glyphicon-download:before {
	content: "\e026";
	}
	.glyphicon-upload:before {
	content: "\e027";
	}
	.glyphicon-inbox:before {
	content: "\e028";
	}
	.glyphicon-play-circle:before {
	content: "\e029";
	}
	.glyphicon-repeat:before {
	content: "\e030";
	}
	.glyphicon-refresh:before {
	content: "\e031";
	}
	.glyphicon-list-alt:before {
	content: "\e032";
	}
	.glyphicon-lock:before {
	content: "\e033";
	}
	.glyphicon-flag:before {
	content: "\e034";
	}
	.glyphicon-headphones:before {
	content: "\e035";
	}
	.glyphicon-volume-off:before {
	content: "\e036";
	}
	.glyphicon-volume-down:before {
	content: "\e037";
	}
	.glyphicon-volume-up:before {
	content: "\e038";
	}
	.glyphicon-qrcode:before {
	content: "\e039";
	}
	.glyphicon-barcode:before {
	content: "\e040";
	}
	.glyphicon-tag:before {
	content: "\e041";
	}
	.glyphicon-tags:before {
	content: "\e042";
	}
	.glyphicon-book:before {
	content: "\e043";
	}
	.glyphicon-bookmark:before {
	content: "\e044";
	}
	.glyphicon-print:before {
	content: "\e045";
	}
	.glyphicon-camera:before {
	content: "\e046";
	}
	.glyphicon-font:before {
	content: "\e047";
	}
	.glyphicon-bold:before {
	content: "\e048";
	}
	.glyphicon-italic:before {
	content: "\e049";
	}
	.glyphicon-text-height:before {
	content: "\e050";
	}
	.glyphicon-text-width:before {
	content: "\e051";
	}
	.glyphicon-align-left:before {
	content: "\e052";
	}
	.glyphicon-align-center:before {
	content: "\e053";
	}
	.glyphicon-align-right:before {
	content: "\e054";
	}
	.glyphicon-align-justify:before {
	content: "\e055";
	}
	.glyphicon-list:before {
	content: "\e056";
	}
	.glyphicon-indent-left:before {
	content: "\e057";
	}
	.glyphicon-indent-right:before {
	content: "\e058";
	}
	.glyphicon-facetime-video:before {
	content: "\e059";
	}
	.glyphicon-picture:before {
	content: "\e060";
	}
	.glyphicon-map-marker:before {
	content: "\e062";
	}
	.glyphicon-adjust:before {
	content: "\e063";
	}
	.glyphicon-tint:before {
	content: "\e064";
	}
	.glyphicon-edit:before {
	content: "\e065";
	}
	.glyphicon-share:before {
	content: "\e066";
	}
	.glyphicon-check:before {
	content: "\e067";
	}
	.glyphicon-move:before {
	content: "\e068";
	}
	.glyphicon-step-backward:before {
	content: "\e069";
	}
	.glyphicon-fast-backward:before {
	content: "\e070";
	}
	.glyphicon-backward:before {
	content: "\e071";
	}
	.glyphicon-play:before {
	content: "\e072";
	}
	.glyphicon-pause:before {
	content: "\e073";
	}
	.glyphicon-stop:before {
	content: "\e074";
	}
	.glyphicon-forward:before {
	content: "\e075";
	}
	.glyphicon-fast-forward:before {
	content: "\e076";
	}
	.glyphicon-step-forward:before {
	content: "\e077";
	}
	.glyphicon-eject:before {
	content: "\e078";
	}
	.glyphicon-chevron-left:before {
	content: "\e079";
	}
	.glyphicon-chevron-right:before {
	content: "\e080";
	}
	.glyphicon-plus-sign:before {
	content: "\e081";
	}
	.glyphicon-minus-sign:before {
	content: "\e082";
	}
	.glyphicon-remove-sign:before {
	content: "\e083";
	}
	.glyphicon-ok-sign:before {
	content: "\e084";
	}
	.glyphicon-question-sign:before {
	content: "\e085";
	}
	.glyphicon-info-sign:before {
	content: "\e086";
	}
	.glyphicon-screenshot:before {
	content: "\e087";
	}
	.glyphicon-remove-circle:before {
	content: "\e088";
	}
	.glyphicon-ok-circle:before {
	content: "\e089";
	}
	.glyphicon-ban-circle:before {
	content: "\e090";
	}
	.glyphicon-arrow-left:before {
	content: "\e091";
	}
	.glyphicon-arrow-right:before {
	content: "\e092";
	}
	.glyphicon-arrow-up:before {
	content: "\e093";
	}
	.glyphicon-arrow-down:before {
	content: "\e094";
	}
	.glyphicon-share-alt:before {
	content: "\e095";
	}
	.glyphicon-resize-full:before {
	content: "\e096";
	}
	.glyphicon-resize-small:before {
	content: "\e097";
	}
	.glyphicon-exclamation-sign:before {
	content: "\e101";
	}
	.glyphicon-gift:before {
	content: "\e102";
	}
	.glyphicon-leaf:before {
	content: "\e103";
	}
	.glyphicon-fire:before {
	content: "\e104";
	}
	.glyphicon-eye-open:before {
	content: "\e105";
	}
	.glyphicon-eye-close:before {
	content: "\e106";
	}
	.glyphicon-warning-sign:before {
	content: "\e107";
	}
	.glyphicon-plane:before {
	content: "\e108";
	}
	.glyphicon-calendar:before {
	content: "\e109";
	}
	.glyphicon-random:before {
	content: "\e110";
	}
	.glyphicon-comment:before {
	content: "\e111";
	}
	.glyphicon-magnet:before {
	content: "\e112";
	}
	.glyphicon-chevron-up:before {
	content: "\e113";
	}
	.glyphicon-chevron-down:before {
	content: "\e114";
	}
	.glyphicon-retweet:before {
	content: "\e115";
	}
	.glyphicon-shopping-cart:before {
	content: "\e116";
	}
	.glyphicon-folder-close:before {
	content: "\e117";
	}
	.glyphicon-folder-open:before {
	content: "\e118";
	}
	.glyphicon-resize-vertical:before {
	content: "\e119";
	}
	.glyphicon-resize-horizontal:before {
	content: "\e120";
	}
	.glyphicon-hdd:before {
	content: "\e121";
	}
	.glyphicon-bullhorn:before {
	content: "\e122";
	}
	.glyphicon-bell:before {
	content: "\e123";
	}
	.glyphicon-certificate:before {
	content: "\e124";
	}
	.glyphicon-thumbs-up:before {
	content: "\e125";
	}
	.glyphicon-thumbs-down:before {
	content: "\e126";
	}
	.glyphicon-hand-right:before {
	content: "\e127";
	}
	.glyphicon-hand-left:before {
	content: "\e128";
	}
	.glyphicon-hand-up:before {
	content: "\e129";
	}
	.glyphicon-hand-down:before {
	content: "\e130";
	}
	.glyphicon-circle-arrow-right:before {
	content: "\e131";
	}
	.glyphicon-circle-arrow-left:before {
	content: "\e132";
	}
	.glyphicon-circle-arrow-up:before {
	content: "\e133";
	}
	.glyphicon-circle-arrow-down:before {
	content: "\e134";
	}
	.glyphicon-globe:before {
	content: "\e135";
	}
	.glyphicon-wrench:before {
	content: "\e136";
	}
	.glyphicon-tasks:before {
	content: "\e137";
	}
	.glyphicon-filter:before {
	content: "\e138";
	}
	.glyphicon-briefcase:before {
	content: "\e139";
	}
	.glyphicon-fullscreen:before {
	content: "\e140";
	}
	.glyphicon-dashboard:before {
	content: "\e141";
	}
	.glyphicon-paperclip:before {
	content: "\e142";
	}
	.glyphicon-heart-empty:before {
	content: "\e143";
	}
	.glyphicon-link:before {
	content: "\e144";
	}
	.glyphicon-phone:before {
	content: "\e145";
	}
	.glyphicon-pushpin:before {
	content: "\e146";
	}
	.glyphicon-usd:before {
	content: "\e148";
	}
	.glyphicon-gbp:before {
	content: "\e149";
	}
	.glyphicon-sort:before {
	content: "\e150";
	}
	.glyphicon-sort-by-alphabet:before {
	content: "\e151";
	}
	.glyphicon-sort-by-alphabet-alt:before {
	content: "\e152";
	}
	.glyphicon-sort-by-order:before {
	content: "\e153";
	}
	.glyphicon-sort-by-order-alt:before {
	content: "\e154";
	}
	.glyphicon-sort-by-attributes:before {
	content: "\e155";
	}
	.glyphicon-sort-by-attributes-alt:before {
	content: "\e156";
	}
	.glyphicon-unchecked:before {
	content: "\e157";
	}
	.glyphicon-expand:before {
	content: "\e158";
	}
	.glyphicon-collapse-down:before {
	content: "\e159";
	}
	.glyphicon-collapse-up:before {
	content: "\e160";
	}
	.glyphicon-log-in:before {
	content: "\e161";
	}
	.glyphicon-flash:before {
	content: "\e162";
	}
	.glyphicon-log-out:before {
	content: "\e163";
	}
	.glyphicon-new-window:before {
	content: "\e164";
	}
	.glyphicon-record:before {
	content: "\e165";
	}
	.glyphicon-save:before {
	content: "\e166";
	}
	.glyphicon-open:before {
	content: "\e167";
	}
	.glyphicon-saved:before {
	content: "\e168";
	}
	.glyphicon-import:before {
	content: "\e169";
	}
	.glyphicon-export:before {
	content: "\e170";
	}
	.glyphicon-send:before {
	content: "\e171";
	}
	.glyphicon-floppy-disk:before {
	content: "\e172";
	}
	.glyphicon-floppy-saved:before {
	content: "\e173";
	}
	.glyphicon-floppy-remove:before {
	content: "\e174";
	}
	.glyphicon-floppy-save:before {
	content: "\e175";
	}
	.glyphicon-floppy-open:before {
	content: "\e176";
	}
	.glyphicon-credit-card:before {
	content: "\e177";
	}
	.glyphicon-transfer:before {
	content: "\e178";
	}
	.glyphicon-cutlery:before {
	content: "\e179";
	}
	.glyphicon-header:before {
	content: "\e180";
	}
	.glyphicon-compressed:before {
	content: "\e181";
	}
	.glyphicon-earphone:before {
	content: "\e182";
	}
	.glyphicon-phone-alt:before {
	content: "\e183";
	}
	.glyphicon-tower:before {
	content: "\e184";
	}
	.glyphicon-stats:before {
	content: "\e185";
	}
	.glyphicon-sd-video:before {
	content: "\e186";
	}
	.glyphicon-hd-video:before {
	content: "\e187";
	}
	.glyphicon-subtitles:before {
	content: "\e188";
	}
	.glyphicon-sound-stereo:before {
	content: "\e189";
	}
	.glyphicon-sound-dolby:before {
	content: "\e190";
	}
	.glyphicon-sound-5-1:before {
	content: "\e191";
	}
	.glyphicon-sound-6-1:before {
	content: "\e192";
	}
	.glyphicon-sound-7-1:before {
	content: "\e193";
	}
	.glyphicon-copyright-mark:before {
	content: "\e194";
	}
	.glyphicon-registration-mark:before {
	content: "\e195";
	}
	.glyphicon-cloud-download:before {
	content: "\e197";
	}
	.glyphicon-cloud-upload:before {
	content: "\e198";
	}
	.glyphicon-tree-conifer:before {
	content: "\e199";
	}
	.glyphicon-tree-deciduous:before {
	content: "\e200";
	}
	.glyphicon-cd:before {
	content: "\e201";
	}
	.glyphicon-save-file:before {
	content: "\e202";
	}
	.glyphicon-open-file:before {
	content: "\e203";
	}
	.glyphicon-level-up:before {
	content: "\e204";
	}
	.glyphicon-copy:before {
	content: "\e205";
	}
	.glyphicon-paste:before {
	content: "\e206";
	}
	.glyphicon-alert:before {
	content: "\e209";
	}
	.glyphicon-equalizer:before {
	content: "\e210";
	}
	.glyphicon-king:before {
	content: "\e211";
	}
	.glyphicon-queen:before {
	content: "\e212";
	}
	.glyphicon-pawn:before {
	content: "\e213";
	}
	.glyphicon-bishop:before {
	content: "\e214";
	}
	.glyphicon-knight:before {
	content: "\e215";
	}
	.glyphicon-baby-formula:before {
	content: "\e216";
	}
	.glyphicon-tent:before {
	content: "\26fa";
	}
	.glyphicon-blackboard:before {
	content: "\e218";
	}
	.glyphicon-bed:before {
	content: "\e219";
	}
	.glyphicon-apple:before {
	content: "\f8ff";
	}
	.glyphicon-erase:before {
	content: "\e221";
	}
	.glyphicon-hourglass:before {
	content: "\231b";
	}
	.glyphicon-lamp:before {
	content: "\e223";
	}
	.glyphicon-duplicate:before {
	content: "\e224";
	}
	.glyphicon-piggy-bank:before {
	content: "\e225";
	}
	.glyphicon-scissors:before {
	content: "\e226";
	}
	.glyphicon-bitcoin:before {
	content: "\e227";
	}
	.glyphicon-btc:before {
	content: "\e227";
	}
	.glyphicon-xbt:before {
	content: "\e227";
	}
	.glyphicon-yen:before {
	content: "\00a5";
	}
	.glyphicon-jpy:before {
	content: "\00a5";
	}
	.glyphicon-ruble:before {
	content: "\20bd";
	}
	.glyphicon-rub:before {
	content: "\20bd";
	}
	.glyphicon-scale:before {
	content: "\e230";
	}
	.glyphicon-ice-lolly:before {
	content: "\e231";
	}
	.glyphicon-ice-lolly-tasted:before {
	content: "\e232";
	}
	.glyphicon-education:before {
	content: "\e233";
	}
	.glyphicon-option-horizontal:before {
	content: "\e234";
	}
	.glyphicon-option-vertical:before {
	content: "\e235";
	}
	.glyphicon-menu-hamburger:before {
	content: "\e236";
	}
	.glyphicon-modal-window:before {
	content: "\e237";
	}
	.glyphicon-oil:before {
	content: "\e238";
	}
	.glyphicon-grain:before {
	content: "\e239";
	}
	.glyphicon-sunglasses:before {
	content: "\e240";
	}
	.glyphicon-text-size:before {
	content: "\e241";
	}
	.glyphicon-text-color:before {
	content: "\e242";
	}
	.glyphicon-text-background:before {
	content: "\e243";
	}
	.glyphicon-object-align-top:before {
	content: "\e244";
	}
	.glyphicon-object-align-bottom:before {
	content: "\e245";
	}
	.glyphicon-object-align-horizontal:before {
	content: "\e246";
	}
	.glyphicon-object-align-left:before {
	content: "\e247";
	}
	.glyphicon-object-align-vertical:before {
	content: "\e248";
	}
	.glyphicon-object-align-right:before {
	content: "\e249";
	}
	.glyphicon-triangle-right:before {
	content: "\e250";
	}
	.glyphicon-triangle-left:before {
	content: "\e251";
	}
	.glyphicon-triangle-bottom:before {
	content: "\e252";
	}
	.glyphicon-triangle-top:before {
	content: "\e253";
	}
	.glyphicon-console:before {
	content: "\e254";
	}
	.glyphicon-superscript:before {
	content: "\e255";
	}
	.glyphicon-subscript:before {
	content: "\e256";
	}
	.glyphicon-menu-left:before {
	content: "\e257";
	}
	.glyphicon-menu-right:before {
	content: "\e258";
	}
	.glyphicon-menu-down:before {
	content: "\e259";
	}
	.glyphicon-menu-up:before {
	content: "\e260";
	}
	* {
	-webkit-box-sizing: border-box;
	-moz-box-sizing: border-box;
	box-sizing: border-box;
	}
	*:before,
	*:after {
	-webkit-box-sizing: border-box;
	-moz-box-sizing: border-box;
	box-sizing: border-box;
	}
	html {
	font-size: 10px;
	-webkit-tap-highlight-color: rgba(0, 0, 0, 0);
	}
	body {
	font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
	font-size: 13px;
	line-height: 1.42857143;
	color: #000;
	background-color: #fff;
	}
	input,
	button,
	select,
	textarea {
	font-family: inherit;
	font-size: inherit;
	line-height: inherit;
	}
	a {
	color: #337ab7;
	text-decoration: none;
	}
	a:hover,
	a:focus {
	color: #23527c;
	text-decoration: underline;
	}
	a:focus {
	outline: 5px auto -webkit-focus-ring-color;
	outline-offset: -2px;
	}
	figure {
	margin: 0;
	}
	img {
	vertical-align: middle;
	}
	.img-responsive,
	.thumbnail > img,
	.thumbnail a > img,
	.carousel-inner > .item > img,
	.carousel-inner > .item > a > img {
	display: block;
	max-width: 100%;
	height: auto;
	}
	.img-rounded {
	border-radius: 3px;
	}
	.img-thumbnail {
	padding: 4px;
	line-height: 1.42857143;
	background-color: #fff;
	border: 1px solid #ddd;
	border-radius: 2px;
	-webkit-transition: all 0.2s ease-in-out;
	-o-transition: all 0.2s ease-in-out;
	transition: all 0.2s ease-in-out;
	display: inline-block;
	max-width: 100%;
	height: auto;
	}
	.img-circle {
	border-radius: 50%;
	}
	hr {
	margin-top: 18px;
	margin-bottom: 18px;
	border: 0;
	border-top: 1px solid #eeeeee;
	}
	.sr-only {
	position: absolute;
	width: 1px;
	height: 1px;
	margin: -1px;
	padding: 0;
	overflow: hidden;
	clip: rect(0, 0, 0, 0);
	border: 0;
	}
	.sr-only-focusable:active,
	.sr-only-focusable:focus {
	position: static;
	width: auto;
	height: auto;
	margin: 0;
	overflow: visible;
	clip: auto;
	}
	[role="button"] {
	cursor: pointer;
	}
	h1,
	h2,
	h3,
	h4,
	h5,
	h6,
	.h1,
	.h2,
	.h3,
	.h4,
	.h5,
	.h6 {
	font-family: inherit;
	font-weight: 500;
	line-height: 1.1;
	color: inherit;
	}
	h1 small,
	h2 small,
	h3 small,
	h4 small,
	h5 small,
	h6 small,
	.h1 small,
	.h2 small,
	.h3 small,
	.h4 small,
	.h5 small,
	.h6 small,
	h1 .small,
	h2 .small,
	h3 .small,
	h4 .small,
	h5 .small,
	h6 .small,
	.h1 .small,
	.h2 .small,
	.h3 .small,
	.h4 .small,
	.h5 .small,
	.h6 .small {
	font-weight: normal;
	line-height: 1;
	color: #777777;
	}
	h1,
	.h1,
	h2,
	.h2,
	h3,
	.h3 {
	margin-top: 18px;
	margin-bottom: 9px;
	}
	h1 small,
	.h1 small,
	h2 small,
	.h2 small,
	h3 small,
	.h3 small,
	h1 .small,
	.h1 .small,
	h2 .small,
	.h2 .small,
	h3 .small,
	.h3 .small {
	font-size: 65%;
	}
	h4,
	.h4,
	h5,
	.h5,
	h6,
	.h6 {
	margin-top: 9px;
	margin-bottom: 9px;
	}
	h4 small,
	.h4 small,
	h5 small,
	.h5 small,
	h6 small,
	.h6 small,
	h4 .small,
	.h4 .small,
	h5 .small,
	.h5 .small,
	h6 .small,
	.h6 .small {
	font-size: 75%;
	}
	h1,
	.h1 {
	font-size: 33px;
	}
	h2,
	.h2 {
	font-size: 27px;
	}
	h3,
	.h3 {
	font-size: 23px;
	}
	h4,
	.h4 {
	font-size: 17px;
	}
	h5,
	.h5 {
	font-size: 13px;
	}
	h6,
	.h6 {
	font-size: 12px;
	}
	p {
	margin: 0 0 9px;
	}
	.lead {
	margin-bottom: 18px;
	font-size: 14px;
	font-weight: 300;
	line-height: 1.4;
	}
	@media (min-width: 768px) {
	.lead {
	font-size: 19.5px;
	}
	}
	small,
	.small {
	font-size: 92%;
	}
	mark,
	.mark {
	background-color: #fcf8e3;
	padding: .2em;
	}
	.text-left {
	text-align: left;
	}
	.text-right {
	text-align: right;
	}
	.text-center {
	text-align: center;
	}
	.text-justify {
	text-align: justify;
	}
	.text-nowrap {
	white-space: nowrap;
	}
	.text-lowercase {
	text-transform: lowercase;
	}
	.text-uppercase {
	text-transform: uppercase;
	}
	.text-capitalize {
	text-transform: capitalize;
	}
	.text-muted {
	color: #777777;
	}
	.text-primary {
	color: #337ab7;
	}
	a.text-primary:hover,
	a.text-primary:focus {
	color: #286090;
	}
	.text-success {
	color: #3c763d;
	}
	a.text-success:hover,
	a.text-success:focus {
	color: #2b542c;
	}
	.text-info {
	color: #31708f;
	}
	a.text-info:hover,
	a.text-info:focus {
	color: #245269;
	}
	.text-warning {
	color: #8a6d3b;
	}
	a.text-warning:hover,
	a.text-warning:focus {
	color: #66512c;
	}
	.text-danger {
	color: #a94442;
	}
	a.text-danger:hover,
	a.text-danger:focus {
	color: #843534;
	}
	.bg-primary {
	color: #fff;
	background-color: #337ab7;
	}
	a.bg-primary:hover,
	a.bg-primary:focus {
	background-color: #286090;
	}
	.bg-success {
	background-color: #dff0d8;
	}
	a.bg-success:hover,
	a.bg-success:focus {
	background-color: #c1e2b3;
	}
	.bg-info {
	background-color: #d9edf7;
	}
	a.bg-info:hover,
	a.bg-info:focus {
	background-color: #afd9ee;
	}
	.bg-warning {
	background-color: #fcf8e3;
	}
	a.bg-warning:hover,
	a.bg-warning:focus {
	background-color: #f7ecb5;
	}
	.bg-danger {
	background-color: #f2dede;
	}
	a.bg-danger:hover,
	a.bg-danger:focus {
	background-color: #e4b9b9;
	}
	.page-header {
	padding-bottom: 8px;
	margin: 36px 0 18px;
	border-bottom: 1px solid #eeeeee;
	}
	ul,
	ol {
	margin-top: 0;
	margin-bottom: 9px;
	}
	ul ul,
	ol ul,
	ul ol,
	ol ol {
	margin-bottom: 0;
	}
	.list-unstyled {
	padding-left: 0;
	list-style: none;
	}
	.list-inline {
	padding-left: 0;
	list-style: none;
	margin-left: -5px;
	}
	.list-inline > li {
	display: inline-block;
	padding-left: 5px;
	padding-right: 5px;
	}
	dl {
	margin-top: 0;
	margin-bottom: 18px;
	}
	dt,
	dd {
	line-height: 1.42857143;
	}
	dt {
	font-weight: bold;
	}
	dd {
	margin-left: 0;
	}
	@media (min-width: 541px) {
	.dl-horizontal dt {
	float: left;
	width: 160px;
	clear: left;
	text-align: right;
	overflow: hidden;
	text-overflow: ellipsis;
	white-space: nowrap;
	}
	.dl-horizontal dd {
	margin-left: 180px;
	}
	}
	abbr[title],
	abbr[data-original-title] {
	cursor: help;
	border-bottom: 1px dotted #777777;
	}
	.initialism {
	font-size: 90%;
	text-transform: uppercase;
	}
	blockquote {
	padding: 9px 18px;
	margin: 0 0 18px;
	font-size: inherit;
	border-left: 5px solid #eeeeee;
	}
	blockquote p:last-child,
	blockquote ul:last-child,
	blockquote ol:last-child {
	margin-bottom: 0;
	}
	blockquote footer,
	blockquote small,
	blockquote .small {
	display: block;
	font-size: 80%;
	line-height: 1.42857143;
	color: #777777;
	}
	blockquote footer:before,
	blockquote small:before,
	blockquote .small:before {
	content: '\2014 \00A0';
	}
	.blockquote-reverse,
	blockquote.pull-right {
	padding-right: 15px;
	padding-left: 0;
	border-right: 5px solid #eeeeee;
	border-left: 0;
	text-align: right;
	}
	.blockquote-reverse footer:before,
	blockquote.pull-right footer:before,
	.blockquote-reverse small:before,
	blockquote.pull-right small:before,
	.blockquote-reverse .small:before,
	blockquote.pull-right .small:before {
	content: '';
	}
	.blockquote-reverse footer:after,
	blockquote.pull-right footer:after,
	.blockquote-reverse small:after,
	blockquote.pull-right small:after,
	.blockquote-reverse .small:after,
	blockquote.pull-right .small:after {
	content: '\00A0 \2014';
	}
	address {
	margin-bottom: 18px;
	font-style: normal;
	line-height: 1.42857143;
	}
	code,
	kbd,
	pre,
	samp {
	font-family: monospace;
	}
	code {
	padding: 2px 4px;
	font-size: 90%;
	color: #c7254e;
	background-color: #f9f2f4;
	border-radius: 2px;
	}
	kbd {
	padding: 2px 4px;
	font-size: 90%;
	color: #888;
	background-color: transparent;
	border-radius: 1px;
	box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.25);
	}
	kbd kbd {
	padding: 0;
	font-size: 100%;
	font-weight: bold;
	box-shadow: none;
	}
	pre {
	display: block;
	padding: 8.5px;
	margin: 0 0 9px;
	font-size: 12px;
	line-height: 1.42857143;
	word-break: break-all;
	word-wrap: break-word;
	color: #333333;
	background-color: #f5f5f5;
	border: 1px solid #ccc;
	border-radius: 2px;
	}
	pre code {
	padding: 0;
	font-size: inherit;
	color: inherit;
	white-space: pre-wrap;
	background-color: transparent;
	border-radius: 0;
	}
	.pre-scrollable {
	max-height: 340px;
	overflow-y: scroll;
	}
	.container {
	margin-right: auto;
	margin-left: auto;
	padding-left: 0px;
	padding-right: 0px;
	}
	@media (min-width: 768px) {
	.container {
	width: 768px;
	}
	}
	@media (min-width: 992px) {
	.container {
	width: 940px;
	}
	}
	@media (min-width: 1200px) {
	.container {
	width: 1140px;
	}
	}
	.container-fluid {
	margin-right: auto;
	margin-left: auto;
	padding-left: 0px;
	padding-right: 0px;
	}
	.row {
	margin-left: 0px;
	margin-right: 0px;
	}
	.col-xs-1, .col-sm-1, .col-md-1, .col-lg-1, .col-xs-2, .col-sm-2, .col-md-2, .col-lg-2, .col-xs-3, .col-sm-3, .col-md-3, .col-lg-3, .col-xs-4, .col-sm-4, .col-md-4, .col-lg-4, .col-xs-5, .col-sm-5, .col-md-5, .col-lg-5, .col-xs-6, .col-sm-6, .col-md-6, .col-lg-6, .col-xs-7, .col-sm-7, .col-md-7, .col-lg-7, .col-xs-8, .col-sm-8, .col-md-8, .col-lg-8, .col-xs-9, .col-sm-9, .col-md-9, .col-lg-9, .col-xs-10, .col-sm-10, .col-md-10, .col-lg-10, .col-xs-11, .col-sm-11, .col-md-11, .col-lg-11, .col-xs-12, .col-sm-12, .col-md-12, .col-lg-12 {
	position: relative;
	min-height: 1px;
	padding-left: 0px;
	padding-right: 0px;
	}
	.col-xs-1, .col-xs-2, .col-xs-3, .col-xs-4, .col-xs-5, .col-xs-6, .col-xs-7, .col-xs-8, .col-xs-9, .col-xs-10, .col-xs-11, .col-xs-12 {
	float: left;
	}
	.col-xs-12 {
	width: 100%;
	}
	.col-xs-11 {
	width: 91.66666667%;
	}
	.col-xs-10 {
	width: 83.33333333%;
	}
	.col-xs-9 {
	width: 75%;
	}
	.col-xs-8 {
	width: 66.66666667%;
	}
	.col-xs-7 {
	width: 58.33333333%;
	}
	.col-xs-6 {
	width: 50%;
	}
	.col-xs-5 {
	width: 41.66666667%;
	}
	.col-xs-4 {
	width: 33.33333333%;
	}
	.col-xs-3 {
	width: 25%;
	}
	.col-xs-2 {
	width: 16.66666667%;
	}
	.col-xs-1 {
	width: 8.33333333%;
	}
	.col-xs-pull-12 {
	right: 100%;
	}
	.col-xs-pull-11 {
	right: 91.66666667%;
	}
	.col-xs-pull-10 {
	right: 83.33333333%;
	}
	.col-xs-pull-9 {
	right: 75%;
	}
	.col-xs-pull-8 {
	right: 66.66666667%;
	}
	.col-xs-pull-7 {
	right: 58.33333333%;
	}
	.col-xs-pull-6 {
	right: 50%;
	}
	.col-xs-pull-5 {
	right: 41.66666667%;
	}
	.col-xs-pull-4 {
	right: 33.33333333%;
	}
	.col-xs-pull-3 {
	right: 25%;
	}
	.col-xs-pull-2 {
	right: 16.66666667%;
	}
	.col-xs-pull-1 {
	right: 8.33333333%;
	}
	.col-xs-pull-0 {
	right: auto;
	}
	.col-xs-push-12 {
	left: 100%;
	}
	.col-xs-push-11 {
	left: 91.66666667%;
	}
	.col-xs-push-10 {
	left: 83.33333333%;
	}
	.col-xs-push-9 {
	left: 75%;
	}
	.col-xs-push-8 {
	left: 66.66666667%;
	}
	.col-xs-push-7 {
	left: 58.33333333%;
	}
	.col-xs-push-6 {
	left: 50%;
	}
	.col-xs-push-5 {
	left: 41.66666667%;
	}
	.col-xs-push-4 {
	left: 33.33333333%;
	}
	.col-xs-push-3 {
	left: 25%;
	}
	.col-xs-push-2 {
	left: 16.66666667%;
	}
	.col-xs-push-1 {
	left: 8.33333333%;
	}
	.col-xs-push-0 {
	left: auto;
	}
	.col-xs-offset-12 {
	margin-left: 100%;
	}
	.col-xs-offset-11 {
	margin-left: 91.66666667%;
	}
	.col-xs-offset-10 {
	margin-left: 83.33333333%;
	}
	.col-xs-offset-9 {
	margin-left: 75%;
	}
	.col-xs-offset-8 {
	margin-left: 66.66666667%;
	}
	.col-xs-offset-7 {
	margin-left: 58.33333333%;
	}
	.col-xs-offset-6 {
	margin-left: 50%;
	}
	.col-xs-offset-5 {
	margin-left: 41.66666667%;
	}
	.col-xs-offset-4 {
	margin-left: 33.33333333%;
	}
	.col-xs-offset-3 {
	margin-left: 25%;
	}
	.col-xs-offset-2 {
	margin-left: 16.66666667%;
	}
	.col-xs-offset-1 {
	margin-left: 8.33333333%;
	}
	.col-xs-offset-0 {
	margin-left: 0%;
	}
	@media (min-width: 768px) {
	.col-sm-1, .col-sm-2, .col-sm-3, .col-sm-4, .col-sm-5, .col-sm-6, .col-sm-7, .col-sm-8, .col-sm-9, .col-sm-10, .col-sm-11, .col-sm-12 {
	float: left;
	}
	.col-sm-12 {
	width: 100%;
	}
	.col-sm-11 {
	width: 91.66666667%;
	}
	.col-sm-10 {
	width: 83.33333333%;
	}
	.col-sm-9 {
	width: 75%;
	}
	.col-sm-8 {
	width: 66.66666667%;
	}
	.col-sm-7 {
	width: 58.33333333%;
	}
	.col-sm-6 {
	width: 50%;
	}
	.col-sm-5 {
	width: 41.66666667%;
	}
	.col-sm-4 {
	width: 33.33333333%;
	}
	.col-sm-3 {
	width: 25%;
	}
	.col-sm-2 {
	width: 16.66666667%;
	}
	.col-sm-1 {
	width: 8.33333333%;
	}
	.col-sm-pull-12 {
	right: 100%;
	}
	.col-sm-pull-11 {
	right: 91.66666667%;
	}
	.col-sm-pull-10 {
	right: 83.33333333%;
	}
	.col-sm-pull-9 {
	right: 75%;
	}
	.col-sm-pull-8 {
	right: 66.66666667%;
	}
	.col-sm-pull-7 {
	right: 58.33333333%;
	}
	.col-sm-pull-6 {
	right: 50%;
	}
	.col-sm-pull-5 {
	right: 41.66666667%;
	}
	.col-sm-pull-4 {
	right: 33.33333333%;
	}
	.col-sm-pull-3 {
	right: 25%;
	}
	.col-sm-pull-2 {
	right: 16.66666667%;
	}
	.col-sm-pull-1 {
	right: 8.33333333%;
	}
	.col-sm-pull-0 {
	right: auto;
	}
	.col-sm-push-12 {
	left: 100%;
	}
	.col-sm-push-11 {
	left: 91.66666667%;
	}
	.col-sm-push-10 {
	left: 83.33333333%;
	}
	.col-sm-push-9 {
	left: 75%;
	}
	.col-sm-push-8 {
	left: 66.66666667%;
	}
	.col-sm-push-7 {
	left: 58.33333333%;
	}
	.col-sm-push-6 {
	left: 50%;
	}
	.col-sm-push-5 {
	left: 41.66666667%;
	}
	.col-sm-push-4 {
	left: 33.33333333%;
	}
	.col-sm-push-3 {
	left: 25%;
	}
	.col-sm-push-2 {
	left: 16.66666667%;
	}
	.col-sm-push-1 {
	left: 8.33333333%;
	}
	.col-sm-push-0 {
	left: auto;
	}
	.col-sm-offset-12 {
	margin-left: 100%;
	}
	.col-sm-offset-11 {
	margin-left: 91.66666667%;
	}
	.col-sm-offset-10 {
	margin-left: 83.33333333%;
	}
	.col-sm-offset-9 {
	margin-left: 75%;
	}
	.col-sm-offset-8 {
	margin-left: 66.66666667%;
	}
	.col-sm-offset-7 {
	margin-left: 58.33333333%;
	}
	.col-sm-offset-6 {
	margin-left: 50%;
	}
	.col-sm-offset-5 {
	margin-left: 41.66666667%;
	}
	.col-sm-offset-4 {
	margin-left: 33.33333333%;
	}
	.col-sm-offset-3 {
	margin-left: 25%;
	}
	.col-sm-offset-2 {
	margin-left: 16.66666667%;
	}
	.col-sm-offset-1 {
	margin-left: 8.33333333%;
	}
	.col-sm-offset-0 {
	margin-left: 0%;
	}
	}
	@media (min-width: 992px) {
	.col-md-1, .col-md-2, .col-md-3, .col-md-4, .col-md-5, .col-md-6, .col-md-7, .col-md-8, .col-md-9, .col-md-10, .col-md-11, .col-md-12 {
	float: left;
	}
	.col-md-12 {
	width: 100%;
	}
	.col-md-11 {
	width: 91.66666667%;
	}
	.col-md-10 {
	width: 83.33333333%;
	}
	.col-md-9 {
	width: 75%;
	}
	.col-md-8 {
	width: 66.66666667%;
	}
	.col-md-7 {
	width: 58.33333333%;
	}
	.col-md-6 {
	width: 50%;
	}
	.col-md-5 {
	width: 41.66666667%;
	}
	.col-md-4 {
	width: 33.33333333%;
	}
	.col-md-3 {
	width: 25%;
	}
	.col-md-2 {
	width: 16.66666667%;
	}
	.col-md-1 {
	width: 8.33333333%;
	}
	.col-md-pull-12 {
	right: 100%;
	}
	.col-md-pull-11 {
	right: 91.66666667%;
	}
	.col-md-pull-10 {
	right: 83.33333333%;
	}
	.col-md-pull-9 {
	right: 75%;
	}
	.col-md-pull-8 {
	right: 66.66666667%;
	}
	.col-md-pull-7 {
	right: 58.33333333%;
	}
	.col-md-pull-6 {
	right: 50%;
	}
	.col-md-pull-5 {
	right: 41.66666667%;
	}
	.col-md-pull-4 {
	right: 33.33333333%;
	}
	.col-md-pull-3 {
	right: 25%;
	}
	.col-md-pull-2 {
	right: 16.66666667%;
	}
	.col-md-pull-1 {
	right: 8.33333333%;
	}
	.col-md-pull-0 {
	right: auto;
	}
	.col-md-push-12 {
	left: 100%;
	}
	.col-md-push-11 {
	left: 91.66666667%;
	}
	.col-md-push-10 {
	left: 83.33333333%;
	}
	.col-md-push-9 {
	left: 75%;
	}
	.col-md-push-8 {
	left: 66.66666667%;
	}
	.col-md-push-7 {
	left: 58.33333333%;
	}
	.col-md-push-6 {
	left: 50%;
	}
	.col-md-push-5 {
	left: 41.66666667%;
	}
	.col-md-push-4 {
	left: 33.33333333%;
	}
	.col-md-push-3 {
	left: 25%;
	}
	.col-md-push-2 {
	left: 16.66666667%;
	}
	.col-md-push-1 {
	left: 8.33333333%;
	}
	.col-md-push-0 {
	left: auto;
	}
	.col-md-offset-12 {
	margin-left: 100%;
	}
	.col-md-offset-11 {
	margin-left: 91.66666667%;
	}
	.col-md-offset-10 {
	margin-left: 83.33333333%;
	}
	.col-md-offset-9 {
	margin-left: 75%;
	}
	.col-md-offset-8 {
	margin-left: 66.66666667%;
	}
	.col-md-offset-7 {
	margin-left: 58.33333333%;
	}
	.col-md-offset-6 {
	margin-left: 50%;
	}
	.col-md-offset-5 {
	margin-left: 41.66666667%;
	}
	.col-md-offset-4 {
	margin-left: 33.33333333%;
	}
	.col-md-offset-3 {
	margin-left: 25%;
	}
	.col-md-offset-2 {
	margin-left: 16.66666667%;
	}
	.col-md-offset-1 {
	margin-left: 8.33333333%;
	}
	.col-md-offset-0 {
	margin-left: 0%;
	}
	}
	@media (min-width: 1200px) {
	.col-lg-1, .col-lg-2, .col-lg-3, .col-lg-4, .col-lg-5, .col-lg-6, .col-lg-7, .col-lg-8, .col-lg-9, .col-lg-10, .col-lg-11, .col-lg-12 {
	float: left;
	}
	.col-lg-12 {
	width: 100%;
	}
	.col-lg-11 {
	width: 91.66666667%;
	}
	.col-lg-10 {
	width: 83.33333333%;
	}
	.col-lg-9 {
	width: 75%;
	}
	.col-lg-8 {
	width: 66.66666667%;
	}
	.col-lg-7 {
	width: 58.33333333%;
	}
	.col-lg-6 {
	width: 50%;
	}
	.col-lg-5 {
	width: 41.66666667%;
	}
	.col-lg-4 {
	width: 33.33333333%;
	}
	.col-lg-3 {
	width: 25%;
	}
	.col-lg-2 {
	width: 16.66666667%;
	}
	.col-lg-1 {
	width: 8.33333333%;
	}
	.col-lg-pull-12 {
	right: 100%;
	}
	.col-lg-pull-11 {
	right: 91.66666667%;
	}
	.col-lg-pull-10 {
	right: 83.33333333%;
	}
	.col-lg-pull-9 {
	right: 75%;
	}
	.col-lg-pull-8 {
	right: 66.66666667%;
	}
	.col-lg-pull-7 {
	right: 58.33333333%;
	}
	.col-lg-pull-6 {
	right: 50%;
	}
	.col-lg-pull-5 {
	right: 41.66666667%;
	}
	.col-lg-pull-4 {
	right: 33.33333333%;
	}
	.col-lg-pull-3 {
	right: 25%;
	}
	.col-lg-pull-2 {
	right: 16.66666667%;
	}
	.col-lg-pull-1 {
	right: 8.33333333%;
	}
	.col-lg-pull-0 {
	right: auto;
	}
	.col-lg-push-12 {
	left: 100%;
	}
	.col-lg-push-11 {
	left: 91.66666667%;
	}
	.col-lg-push-10 {
	left: 83.33333333%;
	}
	.col-lg-push-9 {
	left: 75%;
	}
	.col-lg-push-8 {
	left: 66.66666667%;
	}
	.col-lg-push-7 {
	left: 58.33333333%;
	}
	.col-lg-push-6 {
	left: 50%;
	}
	.col-lg-push-5 {
	left: 41.66666667%;
	}
	.col-lg-push-4 {
	left: 33.33333333%;
	}
	.col-lg-push-3 {
	left: 25%;
	}
	.col-lg-push-2 {
	left: 16.66666667%;
	}
	.col-lg-push-1 {
	left: 8.33333333%;
	}
	.col-lg-push-0 {
	left: auto;
	}
	.col-lg-offset-12 {
	margin-left: 100%;
	}
	.col-lg-offset-11 {
	margin-left: 91.66666667%;
	}
	.col-lg-offset-10 {
	margin-left: 83.33333333%;
	}
	.col-lg-offset-9 {
	margin-left: 75%;
	}
	.col-lg-offset-8 {
	margin-left: 66.66666667%;
	}
	.col-lg-offset-7 {
	margin-left: 58.33333333%;
	}
	.col-lg-offset-6 {
	margin-left: 50%;
	}
	.col-lg-offset-5 {
	margin-left: 41.66666667%;
	}
	.col-lg-offset-4 {
	margin-left: 33.33333333%;
	}
	.col-lg-offset-3 {
	margin-left: 25%;
	}
	.col-lg-offset-2 {
	margin-left: 16.66666667%;
	}
	.col-lg-offset-1 {
	margin-left: 8.33333333%;
	}
	.col-lg-offset-0 {
	margin-left: 0%;
	}
	}
	table {
	background-color: transparent;
	}
	caption {
	padding-top: 8px;
	padding-bottom: 8px;
	color: #777777;
	text-align: left;
	}
	th {
	text-align: left;
	}
	.table {
	width: 100%;
	max-width: 100%;
	margin-bottom: 18px;
	}
	.table > thead > tr > th,
	.table > tbody > tr > th,
	.table > tfoot > tr > th,
	.table > thead > tr > td,
	.table > tbody > tr > td,
	.table > tfoot > tr > td {
	padding: 8px;
	line-height: 1.42857143;
	vertical-align: top;
	border-top: 1px solid #ddd;
	}
	.table > thead > tr > th {
	vertical-align: bottom;
	border-bottom: 2px solid #ddd;
	}
	.table > caption + thead > tr:first-child > th,
	.table > colgroup + thead > tr:first-child > th,
	.table > thead:first-child > tr:first-child > th,
	.table > caption + thead > tr:first-child > td,
	.table > colgroup + thead > tr:first-child > td,
	.table > thead:first-child > tr:first-child > td {
	border-top: 0;
	}
	.table > tbody + tbody {
	border-top: 2px solid #ddd;
	}
	.table .table {
	background-color: #fff;
	}
	.table-condensed > thead > tr > th,
	.table-condensed > tbody > tr > th,
	.table-condensed > tfoot > tr > th,
	.table-condensed > thead > tr > td,
	.table-condensed > tbody > tr > td,
	.table-condensed > tfoot > tr > td {
	padding: 5px;
	}
	.table-bordered {
	border: 1px solid #ddd;
	}
	.table-bordered > thead > tr > th,
	.table-bordered > tbody > tr > th,
	.table-bordered > tfoot > tr > th,
	.table-bordered > thead > tr > td,
	.table-bordered > tbody > tr > td,
	.table-bordered > tfoot > tr > td {
	border: 1px solid #ddd;
	}
	.table-bordered > thead > tr > th,
	.table-bordered > thead > tr > td {
	border-bottom-width: 2px;
	}
	.table-striped > tbody > tr:nth-of-type(odd) {
	background-color: #f9f9f9;
	}
	.table-hover > tbody > tr:hover {
	background-color: #f5f5f5;
	}
	table col[class*="col-"] {
	position: static;
	float: none;
	display: table-column;
	}
	table td[class*="col-"],
	table th[class*="col-"] {
	position: static;
	float: none;
	display: table-cell;
	}
	.table > thead > tr > td.active,
	.table > tbody > tr > td.active,
	.table > tfoot > tr > td.active,
	.table > thead > tr > th.active,
	.table > tbody > tr > th.active,
	.table > tfoot > tr > th.active,
	.table > thead > tr.active > td,
	.table > tbody > tr.active > td,
	.table > tfoot > tr.active > td,
	.table > thead > tr.active > th,
	.table > tbody > tr.active > th,
	.table > tfoot > tr.active > th {
	background-color: #f5f5f5;
	}
	.table-hover > tbody > tr > td.active:hover,
	.table-hover > tbody > tr > th.active:hover,
	.table-hover > tbody > tr.active:hover > td,
	.table-hover > tbody > tr:hover > .active,
	.table-hover > tbody > tr.active:hover > th {
	background-color: #e8e8e8;
	}
	.table > thead > tr > td.success,
	.table > tbody > tr > td.success,
	.table > tfoot > tr > td.success,
	.table > thead > tr > th.success,
	.table > tbody > tr > th.success,
	.table > tfoot > tr > th.success,
	.table > thead > tr.success > td,
	.table > tbody > tr.success > td,
	.table > tfoot > tr.success > td,
	.table > thead > tr.success > th,
	.table > tbody > tr.success > th,
	.table > tfoot > tr.success > th {
	background-color: #dff0d8;
	}
	.table-hover > tbody > tr > td.success:hover,
	.table-hover > tbody > tr > th.success:hover,
	.table-hover > tbody > tr.success:hover > td,
	.table-hover > tbody > tr:hover > .success,
	.table-hover > tbody > tr.success:hover > th {
	background-color: #d0e9c6;
	}
	.table > thead > tr > td.info,
	.table > tbody > tr > td.info,
	.table > tfoot > tr > td.info,
	.table > thead > tr > th.info,
	.table > tbody > tr > th.info,
	.table > tfoot > tr > th.info,
	.table > thead > tr.info > td,
	.table > tbody > tr.info > td,
	.table > tfoot > tr.info > td,
	.table > thead > tr.info > th,
	.table > tbody > tr.info > th,
	.table > tfoot > tr.info > th {
	background-color: #d9edf7;
	}
	.table-hover > tbody > tr > td.info:hover,
	.table-hover > tbody > tr > th.info:hover,
	.table-hover > tbody > tr.info:hover > td,
	.table-hover > tbody > tr:hover > .info,
	.table-hover > tbody > tr.info:hover > th {
	background-color: #c4e3f3;
	}
	.table > thead > tr > td.warning,
	.table > tbody > tr > td.warning,
	.table > tfoot > tr > td.warning,
	.table > thead > tr > th.warning,
	.table > tbody > tr > th.warning,
	.table > tfoot > tr > th.warning,
	.table > thead > tr.warning > td,
	.table > tbody > tr.warning > td,
	.table > tfoot > tr.warning > td,
	.table > thead > tr.warning > th,
	.table > tbody > tr.warning > th,
	.table > tfoot > tr.warning > th {
	background-color: #fcf8e3;
	}
	.table-hover > tbody > tr > td.warning:hover,
	.table-hover > tbody > tr > th.warning:hover,
	.table-hover > tbody > tr.warning:hover > td,
	.table-hover > tbody > tr:hover > .warning,
	.table-hover > tbody > tr.warning:hover > th {
	background-color: #faf2cc;
	}
	.table > thead > tr > td.danger,
	.table > tbody > tr > td.danger,
	.table > tfoot > tr > td.danger,
	.table > thead > tr > th.danger,
	.table > tbody > tr > th.danger,
	.table > tfoot > tr > th.danger,
	.table > thead > tr.danger > td,
	.table > tbody > tr.danger > td,
	.table > tfoot > tr.danger > td,
	.table > thead > tr.danger > th,
	.table > tbody > tr.danger > th,
	.table > tfoot > tr.danger > th {
	background-color: #f2dede;
	}
	.table-hover > tbody > tr > td.danger:hover,
	.table-hover > tbody > tr > th.danger:hover,
	.table-hover > tbody > tr.danger:hover > td,
	.table-hover > tbody > tr:hover > .danger,
	.table-hover > tbody > tr.danger:hover > th {
	background-color: #ebcccc;
	}
	.table-responsive {
	overflow-x: auto;
	min-height: 0.01%;
	}
	@media screen and (max-width: 767px) {
	.table-responsive {
	width: 100%;
	margin-bottom: 13.5px;
	overflow-y: hidden;
	-ms-overflow-style: -ms-autohiding-scrollbar;
	border: 1px solid #ddd;
	}
	.table-responsive > .table {
	margin-bottom: 0;
	}
	.table-responsive > .table > thead > tr > th,
	.table-responsive > .table > tbody > tr > th,
	.table-responsive > .table > tfoot > tr > th,
	.table-responsive > .table > thead > tr > td,
	.table-responsive > .table > tbody > tr > td,
	.table-responsive > .table > tfoot > tr > td {
	white-space: nowrap;
	}
	.table-responsive > .table-bordered {
	border: 0;
	}
	.table-responsive > .table-bordered > thead > tr > th:first-child,
	.table-responsive > .table-bordered > tbody > tr > th:first-child,
	.table-responsive > .table-bordered > tfoot > tr > th:first-child,
	.table-responsive > .table-bordered > thead > tr > td:first-child,
	.table-responsive > .table-bordered > tbody > tr > td:first-child,
	.table-responsive > .table-bordered > tfoot > tr > td:first-child {
	border-left: 0;
	}
	.table-responsive > .table-bordered > thead > tr > th:last-child,
	.table-responsive > .table-bordered > tbody > tr > th:last-child,
	.table-responsive > .table-bordered > tfoot > tr > th:last-child,
	.table-responsive > .table-bordered > thead > tr > td:last-child,
	.table-responsive > .table-bordered > tbody > tr > td:last-child,
	.table-responsive > .table-bordered > tfoot > tr > td:last-child {
	border-right: 0;
	}
	.table-responsive > .table-bordered > tbody > tr:last-child > th,
	.table-responsive > .table-bordered > tfoot > tr:last-child > th,
	.table-responsive > .table-bordered > tbody > tr:last-child > td,
	.table-responsive > .table-bordered > tfoot > tr:last-child > td {
	border-bottom: 0;
	}
	}
	fieldset {
	padding: 0;
	margin: 0;
	border: 0;
	min-width: 0;
	}
	legend {
	display: block;
	width: 100%;
	padding: 0;
	margin-bottom: 18px;
	font-size: 19.5px;
	line-height: inherit;
	color: #333333;
	border: 0;
	border-bottom: 1px solid #e5e5e5;
	}
	label {
	display: inline-block;
	max-width: 100%;
	margin-bottom: 5px;
	font-weight: bold;
	}
	input[type="search"] {
	-webkit-box-sizing: border-box;
	-moz-box-sizing: border-box;
	box-sizing: border-box;
	}
	input[type="radio"],
	input[type="checkbox"] {
	margin: 4px 0 0;
	margin-top: 1px \9;
	line-height: normal;
	}
	input[type="file"] {
	display: block;
	}
	input[type="range"] {
	display: block;
	width: 100%;
	}
	select[multiple],
	select[size] {
	height: auto;
	}
	input[type="file"]:focus,
	input[type="radio"]:focus,
	input[type="checkbox"]:focus {
	outline: 5px auto -webkit-focus-ring-color;
	outline-offset: -2px;
	}
	output {
	display: block;
	padding-top: 7px;
	font-size: 13px;
	line-height: 1.42857143;
	color: #555555;
	}
	.form-control {
	display: block;
	width: 100%;
	height: 32px;
	padding: 6px 12px;
	font-size: 13px;
	line-height: 1.42857143;
	color: #555555;
	background-color: #fff;
	background-image: none;
	border: 1px solid #ccc;
	border-radius: 2px;
	-webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
	box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
	-webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
	-o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
	transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
	}
	.form-control:focus {
	border-color: #66afe9;
	outline: 0;
	-webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
	box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
	}
	.form-control::-moz-placeholder {
	color: #999;
	opacity: 1;
	}
	.form-control:-ms-input-placeholder {
	color: #999;
	}
	.form-control::-webkit-input-placeholder {
	color: #999;
	}
	.form-control::-ms-expand {
	border: 0;
	background-color: transparent;
	}
	.form-control[disabled],
	.form-control[readonly],
	fieldset[disabled] .form-control {
	background-color: #eeeeee;
	opacity: 1;
	}
	.form-control[disabled],
	fieldset[disabled] .form-control {
	cursor: not-allowed;
	}
	textarea.form-control {
	height: auto;
	}
	input[type="search"] {
	-webkit-appearance: none;
	}
	@media screen and (-webkit-min-device-pixel-ratio: 0) {
	input[type="date"].form-control,
	input[type="time"].form-control,
	input[type="datetime-local"].form-control,
	input[type="month"].form-control {
	line-height: 32px;
	}
	input[type="date"].input-sm,
	input[type="time"].input-sm,
	input[type="datetime-local"].input-sm,
	input[type="month"].input-sm,
	.input-group-sm input[type="date"],
	.input-group-sm input[type="time"],
	.input-group-sm input[type="datetime-local"],
	.input-group-sm input[type="month"] {
	line-height: 30px;
	}
	input[type="date"].input-lg,
	input[type="time"].input-lg,
	input[type="datetime-local"].input-lg,
	input[type="month"].input-lg,
	.input-group-lg input[type="date"],
	.input-group-lg input[type="time"],
	.input-group-lg input[type="datetime-local"],
	.input-group-lg input[type="month"] {
	line-height: 45px;
	}
	}
	.form-group {
	margin-bottom: 15px;
	}
	.radio,
	.checkbox {
	position: relative;
	display: block;
	margin-top: 10px;
	margin-bottom: 10px;
	}
	.radio label,
	.checkbox label {
	min-height: 18px;
	padding-left: 20px;
	margin-bottom: 0;
	font-weight: normal;
	cursor: pointer;
	}
	.radio input[type="radio"],
	.radio-inline input[type="radio"],
	.checkbox input[type="checkbox"],
	.checkbox-inline input[type="checkbox"] {
	position: absolute;
	margin-left: -20px;
	margin-top: 4px \9;
	}
	.radio + .radio,
	.checkbox + .checkbox {
	margin-top: -5px;
	}
	.radio-inline,
	.checkbox-inline {
	position: relative;
	display: inline-block;
	padding-left: 20px;
	margin-bottom: 0;
	vertical-align: middle;
	font-weight: normal;
	cursor: pointer;
	}
	.radio-inline + .radio-inline,
	.checkbox-inline + .checkbox-inline {
	margin-top: 0;
	margin-left: 10px;
	}
	input[type="radio"][disabled],
	input[type="checkbox"][disabled],
	input[type="radio"].disabled,
	input[type="checkbox"].disabled,
	fieldset[disabled] input[type="radio"],
	fieldset[disabled] input[type="checkbox"] {
	cursor: not-allowed;
	}
	.radio-inline.disabled,
	.checkbox-inline.disabled,
	fieldset[disabled] .radio-inline,
	fieldset[disabled] .checkbox-inline {
	cursor: not-allowed;
	}
	.radio.disabled label,
	.checkbox.disabled label,
	fieldset[disabled] .radio label,
	fieldset[disabled] .checkbox label {
	cursor: not-allowed;
	}
	.form-control-static {
	padding-top: 7px;
	padding-bottom: 7px;
	margin-bottom: 0;
	min-height: 31px;
	}
	.form-control-static.input-lg,
	.form-control-static.input-sm {
	padding-left: 0;
	padding-right: 0;
	}
	.input-sm {
	height: 30px;
	padding: 5px 10px;
	font-size: 12px;
	line-height: 1.5;
	border-radius: 1px;
	}
	select.input-sm {
	height: 30px;
	line-height: 30px;
	}
	textarea.input-sm,
	select[multiple].input-sm {
	height: auto;
	}
	.form-group-sm .form-control {
	height: 30px;
	padding: 5px 10px;
	font-size: 12px;
	line-height: 1.5;
	border-radius: 1px;
	}
	.form-group-sm select.form-control {
	height: 30px;
	line-height: 30px;
	}
	.form-group-sm textarea.form-control,
	.form-group-sm select[multiple].form-control {
	height: auto;
	}
	.form-group-sm .form-control-static {
	height: 30px;
	min-height: 30px;
	padding: 6px 10px;
	font-size: 12px;
	line-height: 1.5;
	}
	.input-lg {
	height: 45px;
	padding: 10px 16px;
	font-size: 17px;
	line-height: 1.3333333;
	border-radius: 3px;
	}
	select.input-lg {
	height: 45px;
	line-height: 45px;
	}
	textarea.input-lg,
	select[multiple].input-lg {
	height: auto;
	}
	.form-group-lg .form-control {
	height: 45px;
	padding: 10px 16px;
	font-size: 17px;
	line-height: 1.3333333;
	border-radius: 3px;
	}
	.form-group-lg select.form-control {
	height: 45px;
	line-height: 45px;
	}
	.form-group-lg textarea.form-control,
	.form-group-lg select[multiple].form-control {
	height: auto;
	}
	.form-group-lg .form-control-static {
	height: 45px;
	min-height: 35px;
	padding: 11px 16px;
	font-size: 17px;
	line-height: 1.3333333;
	}
	.has-feedback {
	position: relative;
	}
	.has-feedback .form-control {
	padding-right: 40px;
	}
	.form-control-feedback {
	position: absolute;
	top: 0;
	right: 0;
	z-index: 2;
	display: block;
	width: 32px;
	height: 32px;
	line-height: 32px;
	text-align: center;
	pointer-events: none;
	}
	.input-lg + .form-control-feedback,
	.input-group-lg + .form-control-feedback,
	.form-group-lg .form-control + .form-control-feedback {
	width: 45px;
	height: 45px;
	line-height: 45px;
	}
	.input-sm + .form-control-feedback,
	.input-group-sm + .form-control-feedback,
	.form-group-sm .form-control + .form-control-feedback {
	width: 30px;
	height: 30px;
	line-height: 30px;
	}
	.has-success .help-block,
	.has-success .control-label,
	.has-success .radio,
	.has-success .checkbox,
	.has-success .radio-inline,
	.has-success .checkbox-inline,
	.has-success.radio label,
	.has-success.checkbox label,
	.has-success.radio-inline label,
	.has-success.checkbox-inline label {
	color: #3c763d;
	}
	.has-success .form-control {
	border-color: #3c763d;
	-webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
	box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
	}
	.has-success .form-control:focus {
	border-color: #2b542c;
	-webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #67b168;
	box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #67b168;
	}
	.has-success .input-group-addon {
	color: #3c763d;
	border-color: #3c763d;
	background-color: #dff0d8;
	}
	.has-success .form-control-feedback {
	color: #3c763d;
	}
	.has-warning .help-block,
	.has-warning .control-label,
	.has-warning .radio,
	.has-warning .checkbox,
	.has-warning .radio-inline,
	.has-warning .checkbox-inline,
	.has-warning.radio label,
	.has-warning.checkbox label,
	.has-warning.radio-inline label,
	.has-warning.checkbox-inline label {
	color: #8a6d3b;
	}
	.has-warning .form-control {
	border-color: #8a6d3b;
	-webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
	box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
	}
	.has-warning .form-control:focus {
	border-color: #66512c;
	-webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #c0a16b;
	box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #c0a16b;
	}
	.has-warning .input-group-addon {
	color: #8a6d3b;
	border-color: #8a6d3b;
	background-color: #fcf8e3;
	}
	.has-warning .form-control-feedback {
	color: #8a6d3b;
	}
	.has-error .help-block,
	.has-error .control-label,
	.has-error .radio,
	.has-error .checkbox,
	.has-error .radio-inline,
	.has-error .checkbox-inline,
	.has-error.radio label,
	.has-error.checkbox label,
	.has-error.radio-inline label,
	.has-error.checkbox-inline label {
	color: #a94442;
	}
	.has-error .form-control {
	border-color: #a94442;
	-webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
	box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
	}
	.has-error .form-control:focus {
	border-color: #843534;
	-webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #ce8483;
	box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #ce8483;
	}
	.has-error .input-group-addon {
	color: #a94442;
	border-color: #a94442;
	background-color: #f2dede;
	}
	.has-error .form-control-feedback {
	color: #a94442;
	}
	.has-feedback label ~ .form-control-feedback {
	top: 23px;
	}
	.has-feedback label.sr-only ~ .form-control-feedback {
	top: 0;
	}
	.help-block {
	display: block;
	margin-top: 5px;
	margin-bottom: 10px;
	color: #404040;
	}
	@media (min-width: 768px) {
	.form-inline .form-group {
	display: inline-block;
	margin-bottom: 0;
	vertical-align: middle;
	}
	.form-inline .form-control {
	display: inline-block;
	width: auto;
	vertical-align: middle;
	}
	.form-inline .form-control-static {
	display: inline-block;
	}
	.form-inline .input-group {
	display: inline-table;
	vertical-align: middle;
	}
	.form-inline .input-group .input-group-addon,
	.form-inline .input-group .input-group-btn,
	.form-inline .input-group .form-control {
	width: auto;
	}
	.form-inline .input-group > .form-control {
	width: 100%;
	}
	.form-inline .control-label {
	margin-bottom: 0;
	vertical-align: middle;
	}
	.form-inline .radio,
	.form-inline .checkbox {
	display: inline-block;
	margin-top: 0;
	margin-bottom: 0;
	vertical-align: middle;
	}
	.form-inline .radio label,
	.form-inline .checkbox label {
	padding-left: 0;
	}
	.form-inline .radio input[type="radio"],
	.form-inline .checkbox input[type="checkbox"] {
	position: relative;
	margin-left: 0;
	}
	.form-inline .has-feedback .form-control-feedback {
	top: 0;
	}
	}
	.form-horizontal .radio,
	.form-horizontal .checkbox,
	.form-horizontal .radio-inline,
	.form-horizontal .checkbox-inline {
	margin-top: 0;
	margin-bottom: 0;
	padding-top: 7px;
	}
	.form-horizontal .radio,
	.form-horizontal .checkbox {
	min-height: 25px;
	}
	.form-horizontal .form-group {
	margin-left: 0px;
	margin-right: 0px;
	}
	@media (min-width: 768px) {
	.form-horizontal .control-label {
	text-align: right;
	margin-bottom: 0;
	padding-top: 7px;
	}
	}
	.form-horizontal .has-feedback .form-control-feedback {
	right: 0px;
	}
	@media (min-width: 768px) {
	.form-horizontal .form-group-lg .control-label {
	padding-top: 11px;
	font-size: 17px;
	}
	}
	@media (min-width: 768px) {
	.form-horizontal .form-group-sm .control-label {
	padding-top: 6px;
	font-size: 12px;
	}
	}
	.btn {
	display: inline-block;
	margin-bottom: 0;
	font-weight: normal;
	text-align: center;
	vertical-align: middle;
	touch-action: manipulation;
	cursor: pointer;
	background-image: none;
	border: 1px solid transparent;
	white-space: nowrap;
	padding: 6px 12px;
	font-size: 13px;
	line-height: 1.42857143;
	border-radius: 2px;
	-webkit-user-select: none;
	-moz-user-select: none;
	-ms-user-select: none;
	user-select: none;
	}
	.btn:focus,
	.btn:active:focus,
	.btn.active:focus,
	.btn.focus,
	.btn:active.focus,
	.btn.active.focus {
	outline: 5px auto -webkit-focus-ring-color;
	outline-offset: -2px;
	}
	.btn:hover,
	.btn:focus,
	.btn.focus {
	color: #333;
	text-decoration: none;
	}
	.btn:active,
	.btn.active {
	outline: 0;
	background-image: none;
	-webkit-box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
	box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
	}
	.btn.disabled,
	.btn[disabled],
	fieldset[disabled] .btn {
	cursor: not-allowed;
	opacity: 0.65;
	filter: alpha(opacity=65);
	-webkit-box-shadow: none;
	box-shadow: none;
	}
	a.btn.disabled,
	fieldset[disabled] a.btn {
	pointer-events: none;
	}
	.btn-default {
	color: #333;
	background-color: #fff;
	border-color: #ccc;
	}
	.btn-default:focus,
	.btn-default.focus {
	color: #333;
	background-color: #e6e6e6;
	border-color: #8c8c8c;
	}
	.btn-default:hover {
	color: #333;
	background-color: #e6e6e6;
	border-color: #adadad;
	}
	.btn-default:active,
	.btn-default.active,
	.open > .dropdown-toggle.btn-default {
	color: #333;
	background-color: #e6e6e6;
	border-color: #adadad;
	}
	.btn-default:active:hover,
	.btn-default.active:hover,
	.open > .dropdown-toggle.btn-default:hover,
	.btn-default:active:focus,
	.btn-default.active:focus,
	.open > .dropdown-toggle.btn-default:focus,
	.btn-default:active.focus,
	.btn-default.active.focus,
	.open > .dropdown-toggle.btn-default.focus {
	color: #333;
	background-color: #d4d4d4;
	border-color: #8c8c8c;
	}
	.btn-default:active,
	.btn-default.active,
	.open > .dropdown-toggle.btn-default {
	background-image: none;
	}
	.btn-default.disabled:hover,
	.btn-default[disabled]:hover,
	fieldset[disabled] .btn-default:hover,
	.btn-default.disabled:focus,
	.btn-default[disabled]:focus,
	fieldset[disabled] .btn-default:focus,
	.btn-default.disabled.focus,
	.btn-default[disabled].focus,
	fieldset[disabled] .btn-default.focus {
	background-color: #fff;
	border-color: #ccc;
	}
	.btn-default .badge {
	color: #fff;
	background-color: #333;
	}
	.btn-primary {
	color: #fff;
	background-color: #337ab7;
	border-color: #2e6da4;
	}
	.btn-primary:focus,
	.btn-primary.focus {
	color: #fff;
	background-color: #286090;
	border-color: #122b40;
	}
	.btn-primary:hover {
	color: #fff;
	background-color: #286090;
	border-color: #204d74;
	}
	.btn-primary:active,
	.btn-primary.active,
	.open > .dropdown-toggle.btn-primary {
	color: #fff;
	background-color: #286090;
	border-color: #204d74;
	}
	.btn-primary:active:hover,
	.btn-primary.active:hover,
	.open > .dropdown-toggle.btn-primary:hover,
	.btn-primary:active:focus,
	.btn-primary.active:focus,
	.open > .dropdown-toggle.btn-primary:focus,
	.btn-primary:active.focus,
	.btn-primary.active.focus,
	.open > .dropdown-toggle.btn-primary.focus {
	color: #fff;
	background-color: #204d74;
	border-color: #122b40;
	}
	.btn-primary:active,
	.btn-primary.active,
	.open > .dropdown-toggle.btn-primary {
	background-image: none;
	}
	.btn-primary.disabled:hover,
	.btn-primary[disabled]:hover,
	fieldset[disabled] .btn-primary:hover,
	.btn-primary.disabled:focus,
	.btn-primary[disabled]:focus,
	fieldset[disabled] .btn-primary:focus,
	.btn-primary.disabled.focus,
	.btn-primary[disabled].focus,
	fieldset[disabled] .btn-primary.focus {
	background-color: #337ab7;
	border-color: #2e6da4;
	}
	.btn-primary .badge {
	color: #337ab7;
	background-color: #fff;
	}
	.btn-success {
	color: #fff;
	background-color: #5cb85c;
	border-color: #4cae4c;
	}
	.btn-success:focus,
	.btn-success.focus {
	color: #fff;
	background-color: #449d44;
	border-color: #255625;
	}
	.btn-success:hover {
	color: #fff;
	background-color: #449d44;
	border-color: #398439;
	}
	.btn-success:active,
	.btn-success.active,
	.open > .dropdown-toggle.btn-success {
	color: #fff;
	background-color: #449d44;
	border-color: #398439;
	}
	.btn-success:active:hover,
	.btn-success.active:hover,
	.open > .dropdown-toggle.btn-success:hover,
	.btn-success:active:focus,
	.btn-success.active:focus,
	.open > .dropdown-toggle.btn-success:focus,
	.btn-success:active.focus,
	.btn-success.active.focus,
	.open > .dropdown-toggle.btn-success.focus {
	color: #fff;
	background-color: #398439;
	border-color: #255625;
	}
	.btn-success:active,
	.btn-success.active,
	.open > .dropdown-toggle.btn-success {
	background-image: none;
	}
	.btn-success.disabled:hover,
	.btn-success[disabled]:hover,
	fieldset[disabled] .btn-success:hover,
	.btn-success.disabled:focus,
	.btn-success[disabled]:focus,
	fieldset[disabled] .btn-success:focus,
	.btn-success.disabled.focus,
	.btn-success[disabled].focus,
	fieldset[disabled] .btn-success.focus {
	background-color: #5cb85c;
	border-color: #4cae4c;
	}
	.btn-success .badge {
	color: #5cb85c;
	background-color: #fff;
	}
	.btn-info {
	color: #fff;
	background-color: #5bc0de;
	border-color: #46b8da;
	}
	.btn-info:focus,
	.btn-info.focus {
	color: #fff;
	background-color: #31b0d5;
	border-color: #1b6d85;
	}
	.btn-info:hover {
	color: #fff;
	background-color: #31b0d5;
	border-color: #269abc;
	}
	.btn-info:active,
	.btn-info.active,
	.open > .dropdown-toggle.btn-info {
	color: #fff;
	background-color: #31b0d5;
	border-color: #269abc;
	}
	.btn-info:active:hover,
	.btn-info.active:hover,
	.open > .dropdown-toggle.btn-info:hover,
	.btn-info:active:focus,
	.btn-info.active:focus,
	.open > .dropdown-toggle.btn-info:focus,
	.btn-info:active.focus,
	.btn-info.active.focus,
	.open > .dropdown-toggle.btn-info.focus {
	color: #fff;
	background-color: #269abc;
	border-color: #1b6d85;
	}
	.btn-info:active,
	.btn-info.active,
	.open > .dropdown-toggle.btn-info {
	background-image: none;
	}
	.btn-info.disabled:hover,
	.btn-info[disabled]:hover,
	fieldset[disabled] .btn-info:hover,
	.btn-info.disabled:focus,
	.btn-info[disabled]:focus,
	fieldset[disabled] .btn-info:focus,
	.btn-info.disabled.focus,
	.btn-info[disabled].focus,
	fieldset[disabled] .btn-info.focus {
	background-color: #5bc0de;
	border-color: #46b8da;
	}
	.btn-info .badge {
	color: #5bc0de;
	background-color: #fff;
	}
	.btn-warning {
	color: #fff;
	background-color: #f0ad4e;
	border-color: #eea236;
	}
	.btn-warning:focus,
	.btn-warning.focus {
	color: #fff;
	background-color: #ec971f;
	border-color: #985f0d;
	}
	.btn-warning:hover {
	color: #fff;
	background-color: #ec971f;
	border-color: #d58512;
	}
	.btn-warning:active,
	.btn-warning.active,
	.open > .dropdown-toggle.btn-warning {
	color: #fff;
	background-color: #ec971f;
	border-color: #d58512;
	}
	.btn-warning:active:hover,
	.btn-warning.active:hover,
	.open > .dropdown-toggle.btn-warning:hover,
	.btn-warning:active:focus,
	.btn-warning.active:focus,
	.open > .dropdown-toggle.btn-warning:focus,
	.btn-warning:active.focus,
	.btn-warning.active.focus,
	.open > .dropdown-toggle.btn-warning.focus {
	color: #fff;
	background-color: #d58512;
	border-color: #985f0d;
	}
	.btn-warning:active,
	.btn-warning.active,
	.open > .dropdown-toggle.btn-warning {
	background-image: none;
	}
	.btn-warning.disabled:hover,
	.btn-warning[disabled]:hover,
	fieldset[disabled] .btn-warning:hover,
	.btn-warning.disabled:focus,
	.btn-warning[disabled]:focus,
	fieldset[disabled] .btn-warning:focus,
	.btn-warning.disabled.focus,
	.btn-warning[disabled].focus,
	fieldset[disabled] .btn-warning.focus {
	background-color: #f0ad4e;
	border-color: #eea236;
	}
	.btn-warning .badge {
	color: #f0ad4e;
	background-color: #fff;
	}
	.btn-danger {
	color: #fff;
	background-color: #d9534f;
	border-color: #d43f3a;
	}
	.btn-danger:focus,
	.btn-danger.focus {
	color: #fff;
	background-color: #c9302c;
	border-color: #761c19;
	}
	.btn-danger:hover {
	color: #fff;
	background-color: #c9302c;
	border-color: #ac2925;
	}
	.btn-danger:active,
	.btn-danger.active,
	.open > .dropdown-toggle.btn-danger {
	color: #fff;
	background-color: #c9302c;
	border-color: #ac2925;
	}
	.btn-danger:active:hover,
	.btn-danger.active:hover,
	.open > .dropdown-toggle.btn-danger:hover,
	.btn-danger:active:focus,
	.btn-danger.active:focus,
	.open > .dropdown-toggle.btn-danger:focus,
	.btn-danger:active.focus,
	.btn-danger.active.focus,
	.open > .dropdown-toggle.btn-danger.focus {
	color: #fff;
	background-color: #ac2925;
	border-color: #761c19;
	}
	.btn-danger:active,
	.btn-danger.active,
	.open > .dropdown-toggle.btn-danger {
	background-image: none;
	}
	.btn-danger.disabled:hover,
	.btn-danger[disabled]:hover,
	fieldset[disabled] .btn-danger:hover,
	.btn-danger.disabled:focus,
	.btn-danger[disabled]:focus,
	fieldset[disabled] .btn-danger:focus,
	.btn-danger.disabled.focus,
	.btn-danger[disabled].focus,
	fieldset[disabled] .btn-danger.focus {
	background-color: #d9534f;
	border-color: #d43f3a;
	}
	.btn-danger .badge {
	color: #d9534f;
	background-color: #fff;
	}
	.btn-link {
	color: #337ab7;
	font-weight: normal;
	border-radius: 0;
	}
	.btn-link,
	.btn-link:active,
	.btn-link.active,
	.btn-link[disabled],
	fieldset[disabled] .btn-link {
	background-color: transparent;
	-webkit-box-shadow: none;
	box-shadow: none;
	}
	.btn-link,
	.btn-link:hover,
	.btn-link:focus,
	.btn-link:active {
	border-color: transparent;
	}
	.btn-link:hover,
	.btn-link:focus {
	color: #23527c;
	text-decoration: underline;
	background-color: transparent;
	}
	.btn-link[disabled]:hover,
	fieldset[disabled] .btn-link:hover,
	.btn-link[disabled]:focus,
	fieldset[disabled] .btn-link:focus {
	color: #777777;
	text-decoration: none;
	}
	.btn-lg,
	.btn-group-lg > .btn {
	padding: 10px 16px;
	font-size: 17px;
	line-height: 1.3333333;
	border-radius: 3px;
	}
	.btn-sm,
	.btn-group-sm > .btn {
	padding: 5px 10px;
	font-size: 12px;
	line-height: 1.5;
	border-radius: 1px;
	}
	.btn-xs,
	.btn-group-xs > .btn {
	padding: 1px 5px;
	font-size: 12px;
	line-height: 1.5;
	border-radius: 1px;
	}
	.btn-block {
	display: block;
	width: 100%;
	}
	.btn-block + .btn-block {
	margin-top: 5px;
	}
	input[type="submit"].btn-block,
	input[type="reset"].btn-block,
	input[type="button"].btn-block {
	width: 100%;
	}
	.fade {
	opacity: 0;
	-webkit-transition: opacity 0.15s linear;
	-o-transition: opacity 0.15s linear;
	transition: opacity 0.15s linear;
	}
	.fade.in {
	opacity: 1;
	}
	.collapse {
	display: none;
	}
	.collapse.in {
	display: block;
	}
	tr.collapse.in {
	display: table-row;
	}
	tbody.collapse.in {
	display: table-row-group;
	}
	.collapsing {
	position: relative;
	height: 0;
	overflow: hidden;
	-webkit-transition-property: height, visibility;
	transition-property: height, visibility;
	-webkit-transition-duration: 0.35s;
	transition-duration: 0.35s;
	-webkit-transition-timing-function: ease;
	transition-timing-function: ease;
	}
	.caret {
	display: inline-block;
	width: 0;
	height: 0;
	margin-left: 2px;
	vertical-align: middle;
	border-top: 4px dashed;
	border-top: 4px solid \9;
	border-right: 4px solid transparent;
	border-left: 4px solid transparent;
	}
	.dropup,
	.dropdown {
	position: relative;
	}
	.dropdown-toggle:focus {
	outline: 0;
	}
	.dropdown-menu {
	position: absolute;
	top: 100%;
	left: 0;
	z-index: 1000;
	display: none;
	float: left;
	min-width: 160px;
	padding: 5px 0;
	margin: 2px 0 0;
	list-style: none;
	font-size: 13px;
	text-align: left;
	background-color: #fff;
	border: 1px solid #ccc;
	border: 1px solid rgba(0, 0, 0, 0.15);
	border-radius: 2px;
	-webkit-box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175);
	box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175);
	background-clip: padding-box;
	}
	.dropdown-menu.pull-right {
	right: 0;
	left: auto;
	}
	.dropdown-menu .divider {
	height: 1px;
	margin: 8px 0;
	overflow: hidden;
	background-color: #e5e5e5;
	}
	.dropdown-menu > li > a {
	display: block;
	padding: 3px 20px;
	clear: both;
	font-weight: normal;
	line-height: 1.42857143;
	color: #333333;
	white-space: nowrap;
	}
	.dropdown-menu > li > a:hover,
	.dropdown-menu > li > a:focus {
	text-decoration: none;
	color: #262626;
	background-color: #f5f5f5;
	}
	.dropdown-menu > .active > a,
	.dropdown-menu > .active > a:hover,
	.dropdown-menu > .active > a:focus {
	color: #fff;
	text-decoration: none;
	outline: 0;
	background-color: #337ab7;
	}
	.dropdown-menu > .disabled > a,
	.dropdown-menu > .disabled > a:hover,
	.dropdown-menu > .disabled > a:focus {
	color: #777777;
	}
	.dropdown-menu > .disabled > a:hover,
	.dropdown-menu > .disabled > a:focus {
	text-decoration: none;
	background-color: transparent;
	background-image: none;
	filter: progid:DXImageTransform.Microsoft.gradient(enabled = false);
	cursor: not-allowed;
	}
	.open > .dropdown-menu {
	display: block;
	}
	.open > a {
	outline: 0;
	}
	.dropdown-menu-right {
	left: auto;
	right: 0;
	}
	.dropdown-menu-left {
	left: 0;
	right: auto;
	}
	.dropdown-header {
	display: block;
	padding: 3px 20px;
	font-size: 12px;
	line-height: 1.42857143;
	color: #777777;
	white-space: nowrap;
	}
	.dropdown-backdrop {
	position: fixed;
	left: 0;
	right: 0;
	bottom: 0;
	top: 0;
	z-index: 990;
	}
	.pull-right > .dropdown-menu {
	right: 0;
	left: auto;
	}
	.dropup .caret,
	.navbar-fixed-bottom .dropdown .caret {
	border-top: 0;
	border-bottom: 4px dashed;
	border-bottom: 4px solid \9;
	content: "";
	}
	.dropup .dropdown-menu,
	.navbar-fixed-bottom .dropdown .dropdown-menu {
	top: auto;
	bottom: 100%;
	margin-bottom: 2px;
	}
	@media (min-width: 541px) {
	.navbar-right .dropdown-menu {
	left: auto;
	right: 0;
	}
	.navbar-right .dropdown-menu-left {
	left: 0;
	right: auto;
	}
	}
	.btn-group,
	.btn-group-vertical {
	position: relative;
	display: inline-block;
	vertical-align: middle;
	}
	.btn-group > .btn,
	.btn-group-vertical > .btn {
	position: relative;
	float: left;
	}
	.btn-group > .btn:hover,
	.btn-group-vertical > .btn:hover,
	.btn-group > .btn:focus,
	.btn-group-vertical > .btn:focus,
	.btn-group > .btn:active,
	.btn-group-vertical > .btn:active,
	.btn-group > .btn.active,
	.btn-group-vertical > .btn.active {
	z-index: 2;
	}
	.btn-group .btn + .btn,
	.btn-group .btn + .btn-group,
	.btn-group .btn-group + .btn,
	.btn-group .btn-group + .btn-group {
	margin-left: -1px;
	}
	.btn-toolbar {
	margin-left: -5px;
	}
	.btn-toolbar .btn,
	.btn-toolbar .btn-group,
	.btn-toolbar .input-group {
	float: left;
	}
	.btn-toolbar > .btn,
	.btn-toolbar > .btn-group,
	.btn-toolbar > .input-group {
	margin-left: 5px;
	}
	.btn-group > .btn:not(:first-child):not(:last-child):not(.dropdown-toggle) {
	border-radius: 0;
	}
	.btn-group > .btn:first-child {
	margin-left: 0;
	}
	.btn-group > .btn:first-child:not(:last-child):not(.dropdown-toggle) {
	border-bottom-right-radius: 0;
	border-top-right-radius: 0;
	}
	.btn-group > .btn:last-child:not(:first-child),
	.btn-group > .dropdown-toggle:not(:first-child) {
	border-bottom-left-radius: 0;
	border-top-left-radius: 0;
	}
	.btn-group > .btn-group {
	float: left;
	}
	.btn-group > .btn-group:not(:first-child):not(:last-child) > .btn {
	border-radius: 0;
	}
	.btn-group > .btn-group:first-child:not(:last-child) > .btn:last-child,
	.btn-group > .btn-group:first-child:not(:last-child) > .dropdown-toggle {
	border-bottom-right-radius: 0;
	border-top-right-radius: 0;
	}
	.btn-group > .btn-group:last-child:not(:first-child) > .btn:first-child {
	border-bottom-left-radius: 0;
	border-top-left-radius: 0;
	}
	.btn-group .dropdown-toggle:active,
	.btn-group.open .dropdown-toggle {
	outline: 0;
	}
	.btn-group > .btn + .dropdown-toggle {
	padding-left: 8px;
	padding-right: 8px;
	}
	.btn-group > .btn-lg + .dropdown-toggle {
	padding-left: 12px;
	padding-right: 12px;
	}
	.btn-group.open .dropdown-toggle {
	-webkit-box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
	box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
	}
	.btn-group.open .dropdown-toggle.btn-link {
	-webkit-box-shadow: none;
	box-shadow: none;
	}
	.btn .caret {
	margin-left: 0;
	}
	.btn-lg .caret {
	border-width: 5px 5px 0;
	border-bottom-width: 0;
	}
	.dropup .btn-lg .caret {
	border-width: 0 5px 5px;
	}
	.btn-group-vertical > .btn,
	.btn-group-vertical > .btn-group,
	.btn-group-vertical > .btn-group > .btn {
	display: block;
	float: none;
	width: 100%;
	max-width: 100%;
	}
	.btn-group-vertical > .btn-group > .btn {
	float: none;
	}
	.btn-group-vertical > .btn + .btn,
	.btn-group-vertical > .btn + .btn-group,
	.btn-group-vertical > .btn-group + .btn,
	.btn-group-vertical > .btn-group + .btn-group {
	margin-top: -1px;
	margin-left: 0;
	}
	.btn-group-vertical > .btn:not(:first-child):not(:last-child) {
	border-radius: 0;
	}
	.btn-group-vertical > .btn:first-child:not(:last-child) {
	border-top-right-radius: 2px;
	border-top-left-radius: 2px;
	border-bottom-right-radius: 0;
	border-bottom-left-radius: 0;
	}
	.btn-group-vertical > .btn:last-child:not(:first-child) {
	border-top-right-radius: 0;
	border-top-left-radius: 0;
	border-bottom-right-radius: 2px;
	border-bottom-left-radius: 2px;
	}
	.btn-group-vertical > .btn-group:not(:first-child):not(:last-child) > .btn {
	border-radius: 0;
	}
	.btn-group-vertical > .btn-group:first-child:not(:last-child) > .btn:last-child,
	.btn-group-vertical > .btn-group:first-child:not(:last-child) > .dropdown-toggle {
	border-bottom-right-radius: 0;
	border-bottom-left-radius: 0;
	}
	.btn-group-vertical > .btn-group:last-child:not(:first-child) > .btn:first-child {
	border-top-right-radius: 0;
	border-top-left-radius: 0;
	}
	.btn-group-justified {
	display: table;
	width: 100%;
	table-layout: fixed;
	border-collapse: separate;
	}
	.btn-group-justified > .btn,
	.btn-group-justified > .btn-group {
	float: none;
	display: table-cell;
	width: 1%;
	}
	.btn-group-justified > .btn-group .btn {
	width: 100%;
	}
	.btn-group-justified > .btn-group .dropdown-menu {
	left: auto;
	}
	[data-toggle="buttons"] > .btn input[type="radio"],
	[data-toggle="buttons"] > .btn-group > .btn input[type="radio"],
	[data-toggle="buttons"] > .btn input[type="checkbox"],
	[data-toggle="buttons"] > .btn-group > .btn input[type="checkbox"] {
	position: absolute;
	clip: rect(0, 0, 0, 0);
	pointer-events: none;
	}
	.input-group {
	position: relative;
	display: table;
	border-collapse: separate;
	}
	.input-group[class*="col-"] {
	float: none;
	padding-left: 0;
	padding-right: 0;
	}
	.input-group .form-control {
	position: relative;
	z-index: 2;
	float: left;
	width: 100%;
	margin-bottom: 0;
	}
	.input-group .form-control:focus {
	z-index: 3;
	}
	.input-group-lg > .form-control,
	.input-group-lg > .input-group-addon,
	.input-group-lg > .input-group-btn > .btn {
	height: 45px;
	padding: 10px 16px;
	font-size: 17px;
	line-height: 1.3333333;
	border-radius: 3px;
	}
	select.input-group-lg > .form-control,
	select.input-group-lg > .input-group-addon,
	select.input-group-lg > .input-group-btn > .btn {
	height: 45px;
	line-height: 45px;
	}
	textarea.input-group-lg > .form-control,
	textarea.input-group-lg > .input-group-addon,
	textarea.input-group-lg > .input-group-btn > .btn,
	select[multiple].input-group-lg > .form-control,
	select[multiple].input-group-lg > .input-group-addon,
	select[multiple].input-group-lg > .input-group-btn > .btn {
	height: auto;
	}
	.input-group-sm > .form-control,
	.input-group-sm > .input-group-addon,
	.input-group-sm > .input-group-btn > .btn {
	height: 30px;
	padding: 5px 10px;
	font-size: 12px;
	line-height: 1.5;
	border-radius: 1px;
	}
	select.input-group-sm > .form-control,
	select.input-group-sm > .input-group-addon,
	select.input-group-sm > .input-group-btn > .btn {
	height: 30px;
	line-height: 30px;
	}
	textarea.input-group-sm > .form-control,
	textarea.input-group-sm > .input-group-addon,
	textarea.input-group-sm > .input-group-btn > .btn,
	select[multiple].input-group-sm > .form-control,
	select[multiple].input-group-sm > .input-group-addon,
	select[multiple].input-group-sm > .input-group-btn > .btn {
	height: auto;
	}
	.input-group-addon,
	.input-group-btn,
	.input-group .form-control {
	display: table-cell;
	}
	.input-group-addon:not(:first-child):not(:last-child),
	.input-group-btn:not(:first-child):not(:last-child),
	.input-group .form-control:not(:first-child):not(:last-child) {
	border-radius: 0;
	}
	.input-group-addon,
	.input-group-btn {
	width: 1%;
	white-space: nowrap;
	vertical-align: middle;
	}
	.input-group-addon {
	padding: 6px 12px;
	font-size: 13px;
	font-weight: normal;
	line-height: 1;
	color: #555555;
	text-align: center;
	background-color: #eeeeee;
	border: 1px solid #ccc;
	border-radius: 2px;
	}
	.input-group-addon.input-sm {
	padding: 5px 10px;
	font-size: 12px;
	border-radius: 1px;
	}
	.input-group-addon.input-lg {
	padding: 10px 16px;
	font-size: 17px;
	border-radius: 3px;
	}
	.input-group-addon input[type="radio"],
	.input-group-addon input[type="checkbox"] {
	margin-top: 0;
	}
	.input-group .form-control:first-child,
	.input-group-addon:first-child,
	.input-group-btn:first-child > .btn,
	.input-group-btn:first-child > .btn-group > .btn,
	.input-group-btn:first-child > .dropdown-toggle,
	.input-group-btn:last-child > .btn:not(:last-child):not(.dropdown-toggle),
	.input-group-btn:last-child > .btn-group:not(:last-child) > .btn {
	border-bottom-right-radius: 0;
	border-top-right-radius: 0;
	}
	.input-group-addon:first-child {
	border-right: 0;
	}
	.input-group .form-control:last-child,
	.input-group-addon:last-child,
	.input-group-btn:last-child > .btn,
	.input-group-btn:last-child > .btn-group > .btn,
	.input-group-btn:last-child > .dropdown-toggle,
	.input-group-btn:first-child > .btn:not(:first-child),
	.input-group-btn:first-child > .btn-group:not(:first-child) > .btn {
	border-bottom-left-radius: 0;
	border-top-left-radius: 0;
	}
	.input-group-addon:last-child {
	border-left: 0;
	}
	.input-group-btn {
	position: relative;
	font-size: 0;
	white-space: nowrap;
	}
	.input-group-btn > .btn {
	position: relative;
	}
	.input-group-btn > .btn + .btn {
	margin-left: -1px;
	}
	.input-group-btn > .btn:hover,
	.input-group-btn > .btn:focus,
	.input-group-btn > .btn:active {
	z-index: 2;
	}
	.input-group-btn:first-child > .btn,
	.input-group-btn:first-child > .btn-group {
	margin-right: -1px;
	}
	.input-group-btn:last-child > .btn,
	.input-group-btn:last-child > .btn-group {
	z-index: 2;
	margin-left: -1px;
	}
	.nav {
	margin-bottom: 0;
	padding-left: 0;
	list-style: none;
	}
	.nav > li {
	position: relative;
	display: block;
	}
	.nav > li > a {
	position: relative;
	display: block;
	padding: 10px 15px;
	}
	.nav > li > a:hover,
	.nav > li > a:focus {
	text-decoration: none;
	background-color: #eeeeee;
	}
	.nav > li.disabled > a {
	color: #777777;
	}
	.nav > li.disabled > a:hover,
	.nav > li.disabled > a:focus {
	color: #777777;
	text-decoration: none;
	background-color: transparent;
	cursor: not-allowed;
	}
	.nav .open > a,
	.nav .open > a:hover,
	.nav .open > a:focus {
	background-color: #eeeeee;
	border-color: #337ab7;
	}
	.nav .nav-divider {
	height: 1px;
	margin: 8px 0;
	overflow: hidden;
	background-color: #e5e5e5;
	}
	.nav > li > a > img {
	max-width: none;
	}
	.nav-tabs {
	border-bottom: 1px solid #ddd;
	}
	.nav-tabs > li {
	float: left;
	margin-bottom: -1px;
	}
	.nav-tabs > li > a {
	margin-right: 2px;
	line-height: 1.42857143;
	border: 1px solid transparent;
	border-radius: 2px 2px 0 0;
	}
	.nav-tabs > li > a:hover {
	border-color: #eeeeee #eeeeee #ddd;
	}
	.nav-tabs > li.active > a,
	.nav-tabs > li.active > a:hover,
	.nav-tabs > li.active > a:focus {
	color: #555555;
	background-color: #fff;
	border: 1px solid #ddd;
	border-bottom-color: transparent;
	cursor: default;
	}
	.nav-tabs.nav-justified {
	width: 100%;
	border-bottom: 0;
	}
	.nav-tabs.nav-justified > li {
	float: none;
	}
	.nav-tabs.nav-justified > li > a {
	text-align: center;
	margin-bottom: 5px;
	}
	.nav-tabs.nav-justified > .dropdown .dropdown-menu {
	top: auto;
	left: auto;
	}
	@media (min-width: 768px) {
	.nav-tabs.nav-justified > li {
	display: table-cell;
	width: 1%;
	}
	.nav-tabs.nav-justified > li > a {
	margin-bottom: 0;
	}
	}
	.nav-tabs.nav-justified > li > a {
	margin-right: 0;
	border-radius: 2px;
	}
	.nav-tabs.nav-justified > .active > a,
	.nav-tabs.nav-justified > .active > a:hover,
	.nav-tabs.nav-justified > .active > a:focus {
	border: 1px solid #ddd;
	}
	@media (min-width: 768px) {
	.nav-tabs.nav-justified > li > a {
	border-bottom: 1px solid #ddd;
	border-radius: 2px 2px 0 0;
	}
	.nav-tabs.nav-justified > .active > a,
	.nav-tabs.nav-justified > .active > a:hover,
	.nav-tabs.nav-justified > .active > a:focus {
	border-bottom-color: #fff;
	}
	}
	.nav-pills > li {
	float: left;
	}
	.nav-pills > li > a {
	border-radius: 2px;
	}
	.nav-pills > li + li {
	margin-left: 2px;
	}
	.nav-pills > li.active > a,
	.nav-pills > li.active > a:hover,
	.nav-pills > li.active > a:focus {
	color: #fff;
	background-color: #337ab7;
	}
	.nav-stacked > li {
	float: none;
	}
	.nav-stacked > li + li {
	margin-top: 2px;
	margin-left: 0;
	}
	.nav-justified {
	width: 100%;
	}
	.nav-justified > li {
	float: none;
	}
	.nav-justified > li > a {
	text-align: center;
	margin-bottom: 5px;
	}
	.nav-justified > .dropdown .dropdown-menu {
	top: auto;
	left: auto;
	}
	@media (min-width: 768px) {
	.nav-justified > li {
	display: table-cell;
	width: 1%;
	}
	.nav-justified > li > a {
	margin-bottom: 0;
	}
	}
	.nav-tabs-justified {
	border-bottom: 0;
	}
	.nav-tabs-justified > li > a {
	margin-right: 0;
	border-radius: 2px;
	}
	.nav-tabs-justified > .active > a,
	.nav-tabs-justified > .active > a:hover,
	.nav-tabs-justified > .active > a:focus {
	border: 1px solid #ddd;
	}
	@media (min-width: 768px) {
	.nav-tabs-justified > li > a {
	border-bottom: 1px solid #ddd;
	border-radius: 2px 2px 0 0;
	}
	.nav-tabs-justified > .active > a,
	.nav-tabs-justified > .active > a:hover,
	.nav-tabs-justified > .active > a:focus {
	border-bottom-color: #fff;
	}
	}
	.tab-content > .tab-pane {
	display: none;
	}
	.tab-content > .active {
	display: block;
	}
	.nav-tabs .dropdown-menu {
	margin-top: -1px;
	border-top-right-radius: 0;
	border-top-left-radius: 0;
	}
	.navbar {
	position: relative;
	min-height: 30px;
	margin-bottom: 18px;
	border: 1px solid transparent;
	}
	@media (min-width: 541px) {
	.navbar {
	border-radius: 2px;
	}
	}
	@media (min-width: 541px) {
	.navbar-header {
	float: left;
	}
	}
	.navbar-collapse {
	overflow-x: visible;
	padding-right: 0px;
	padding-left: 0px;
	border-top: 1px solid transparent;
	box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1);
	-webkit-overflow-scrolling: touch;
	}
	.navbar-collapse.in {
	overflow-y: auto;
	}
	@media (min-width: 541px) {
	.navbar-collapse {
	width: auto;
	border-top: 0;
	box-shadow: none;
	}
	.navbar-collapse.collapse {
	display: block !important;
	height: auto !important;
	padding-bottom: 0;
	overflow: visible !important;
	}
	.navbar-collapse.in {
	overflow-y: visible;
	}
	.navbar-fixed-top .navbar-collapse,
	.navbar-static-top .navbar-collapse,
	.navbar-fixed-bottom .navbar-collapse {
	padding-left: 0;
	padding-right: 0;
	}
	}
	.navbar-fixed-top .navbar-collapse,
	.navbar-fixed-bottom .navbar-collapse {
	max-height: 340px;
	}
	@media (max-device-width: 540px) and (orientation: landscape) {
	.navbar-fixed-top .navbar-collapse,
	.navbar-fixed-bottom .navbar-collapse {
	max-height: 200px;
	}
	}
	.container > .navbar-header,
	.container-fluid > .navbar-header,
	.container > .navbar-collapse,
	.container-fluid > .navbar-collapse {
	margin-right: 0px;
	margin-left: 0px;
	}
	@media (min-width: 541px) {
	.container > .navbar-header,
	.container-fluid > .navbar-header,
	.container > .navbar-collapse,
	.container-fluid > .navbar-collapse {
	margin-right: 0;
	margin-left: 0;
	}
	}
	.navbar-static-top {
	z-index: 1000;
	border-width: 0 0 1px;
	}
	@media (min-width: 541px) {
	.navbar-static-top {
	border-radius: 0;
	}
	}
	.navbar-fixed-top,
	.navbar-fixed-bottom {
	position: fixed;
	right: 0;
	left: 0;
	z-index: 1030;
	}
	@media (min-width: 541px) {
	.navbar-fixed-top,
	.navbar-fixed-bottom {
	border-radius: 0;
	}
	}
	.navbar-fixed-top {
	top: 0;
	border-width: 0 0 1px;
	}
	.navbar-fixed-bottom {
	bottom: 0;
	margin-bottom: 0;
	border-width: 1px 0 0;
	}
	.navbar-brand {
	float: left;
	padding: 6px 0px;
	font-size: 17px;
	line-height: 18px;
	height: 30px;
	}
	.navbar-brand:hover,
	.navbar-brand:focus {
	text-decoration: none;
	}
	.navbar-brand > img {
	display: block;
	}
	@media (min-width: 541px) {
	.navbar > .container .navbar-brand,
	.navbar > .container-fluid .navbar-brand {
	margin-left: 0px;
	}
	}
	.navbar-toggle {
	position: relative;
	float: right;
	margin-right: 0px;
	padding: 9px 10px;
	margin-top: -2px;
	margin-bottom: -2px;
	background-color: transparent;
	background-image: none;
	border: 1px solid transparent;
	border-radius: 2px;
	}
	.navbar-toggle:focus {
	outline: 0;
	}
	.navbar-toggle .icon-bar {
	display: block;
	width: 22px;
	height: 2px;
	border-radius: 1px;
	}
	.navbar-toggle .icon-bar + .icon-bar {
	margin-top: 4px;
	}
	@media (min-width: 541px) {
	.navbar-toggle {
	display: none;
	}
	}
	.navbar-nav {
	margin: 3px 0px;
	}
	.navbar-nav > li > a {
	padding-top: 10px;
	padding-bottom: 10px;
	line-height: 18px;
	}
	@media (max-width: 540px) {
	.navbar-nav .open .dropdown-menu {
	position: static;
	float: none;
	width: auto;
	margin-top: 0;
	background-color: transparent;
	border: 0;
	box-shadow: none;
	}
	.navbar-nav .open .dropdown-menu > li > a,
	.navbar-nav .open .dropdown-menu .dropdown-header {
	padding: 5px 15px 5px 25px;
	}
	.navbar-nav .open .dropdown-menu > li > a {
	line-height: 18px;
	}
	.navbar-nav .open .dropdown-menu > li > a:hover,
	.navbar-nav .open .dropdown-menu > li > a:focus {
	background-image: none;
	}
	}
	@media (min-width: 541px) {
	.navbar-nav {
	float: left;
	margin: 0;
	}
	.navbar-nav > li {
	float: left;
	}
	.navbar-nav > li > a {
	padding-top: 6px;
	padding-bottom: 6px;
	}
	}
	.navbar-form {
	margin-left: 0px;
	margin-right: 0px;
	padding: 10px 0px;
	border-top: 1px solid transparent;
	border-bottom: 1px solid transparent;
	-webkit-box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1), 0 1px 0 rgba(255, 255, 255, 0.1);
	box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1), 0 1px 0 rgba(255, 255, 255, 0.1);
	margin-top: -1px;
	margin-bottom: -1px;
	}
	@media (min-width: 768px) {
	.navbar-form .form-group {
	display: inline-block;
	margin-bottom: 0;
	vertical-align: middle;
	}
	.navbar-form .form-control {
	display: inline-block;
	width: auto;
	vertical-align: middle;
	}
	.navbar-form .form-control-static {
	display: inline-block;
	}
	.navbar-form .input-group {
	display: inline-table;
	vertical-align: middle;
	}
	.navbar-form .input-group .input-group-addon,
	.navbar-form .input-group .input-group-btn,
	.navbar-form .input-group .form-control {
	width: auto;
	}
	.navbar-form .input-group > .form-control {
	width: 100%;
	}
	.navbar-form .control-label {
	margin-bottom: 0;
	vertical-align: middle;
	}
	.navbar-form .radio,
	.navbar-form .checkbox {
	display: inline-block;
	margin-top: 0;
	margin-bottom: 0;
	vertical-align: middle;
	}
	.navbar-form .radio label,
	.navbar-form .checkbox label {
	padding-left: 0;
	}
	.navbar-form .radio input[type="radio"],
	.navbar-form .checkbox input[type="checkbox"] {
	position: relative;
	margin-left: 0;
	}
	.navbar-form .has-feedback .form-control-feedback {
	top: 0;
	}
	}
	@media (max-width: 540px) {
	.navbar-form .form-group {
	margin-bottom: 5px;
	}
	.navbar-form .form-group:last-child {
	margin-bottom: 0;
	}
	}
	@media (min-width: 541px) {
	.navbar-form {
	width: auto;
	border: 0;
	margin-left: 0;
	margin-right: 0;
	padding-top: 0;
	padding-bottom: 0;
	-webkit-box-shadow: none;
	box-shadow: none;
	}
	}
	.navbar-nav > li > .dropdown-menu {
	margin-top: 0;
	border-top-right-radius: 0;
	border-top-left-radius: 0;
	}
	.navbar-fixed-bottom .navbar-nav > li > .dropdown-menu {
	margin-bottom: 0;
	border-top-right-radius: 2px;
	border-top-left-radius: 2px;
	border-bottom-right-radius: 0;
	border-bottom-left-radius: 0;
	}
	.navbar-btn {
	margin-top: -1px;
	margin-bottom: -1px;
	}
	.navbar-btn.btn-sm {
	margin-top: 0px;
	margin-bottom: 0px;
	}
	.navbar-btn.btn-xs {
	margin-top: 4px;
	margin-bottom: 4px;
	}
	.navbar-text {
	margin-top: 6px;
	margin-bottom: 6px;
	}
	@media (min-width: 541px) {
	.navbar-text {
	float: left;
	margin-left: 0px;
	margin-right: 0px;
	}
	}
	@media (min-width: 541px) {
	.navbar-left {
	float: left !important;
	float: left;
	}
	.navbar-right {
	float: right !important;
	float: right;
	margin-right: 0px;
	}
	.navbar-right ~ .navbar-right {
	margin-right: 0;
	}
	}
	.navbar-default {
	background-color: #f8f8f8;
	border-color: #e7e7e7;
	}
	.navbar-default .navbar-brand {
	color: #777;
	}
	.navbar-default .navbar-brand:hover,
	.navbar-default .navbar-brand:focus {
	color: #5e5e5e;
	background-color: transparent;
	}
	.navbar-default .navbar-text {
	color: #777;
	}
	.navbar-default .navbar-nav > li > a {
	color: #777;
	}
	.navbar-default .navbar-nav > li > a:hover,
	.navbar-default .navbar-nav > li > a:focus {
	color: #333;
	background-color: transparent;
	}
	.navbar-default .navbar-nav > .active > a,
	.navbar-default .navbar-nav > .active > a:hover,
	.navbar-default .navbar-nav > .active > a:focus {
	color: #555;
	background-color: #e7e7e7;
	}
	.navbar-default .navbar-nav > .disabled > a,
	.navbar-default .navbar-nav > .disabled > a:hover,
	.navbar-default .navbar-nav > .disabled > a:focus {
	color: #ccc;
	background-color: transparent;
	}
	.navbar-default .navbar-toggle {
	border-color: #ddd;
	}
	.navbar-default .navbar-toggle:hover,
	.navbar-default .navbar-toggle:focus {
	background-color: #ddd;
	}
	.navbar-default .navbar-toggle .icon-bar {
	background-color: #888;
	}
	.navbar-default .navbar-collapse,
	.navbar-default .navbar-form {
	border-color: #e7e7e7;
	}
	.navbar-default .navbar-nav > .open > a,
	.navbar-default .navbar-nav > .open > a:hover,
	.navbar-default .navbar-nav > .open > a:focus {
	background-color: #e7e7e7;
	color: #555;
	}
	@media (max-width: 540px) {
	.navbar-default .navbar-nav .open .dropdown-menu > li > a {
	color: #777;
	}
	.navbar-default .navbar-nav .open .dropdown-menu > li > a:hover,
	.navbar-default .navbar-nav .open .dropdown-menu > li > a:focus {
	color: #333;
	background-color: transparent;
	}
	.navbar-default .navbar-nav .open .dropdown-menu > .active > a,
	.navbar-default .navbar-nav .open .dropdown-menu > .active > a:hover,
	.navbar-default .navbar-nav .open .dropdown-menu > .active > a:focus {
	color: #555;
	background-color: #e7e7e7;
	}
	.navbar-default .navbar-nav .open .dropdown-menu > .disabled > a,
	.navbar-default .navbar-nav .open .dropdown-menu > .disabled > a:hover,
	.navbar-default .navbar-nav .open .dropdown-menu > .disabled > a:focus {
	color: #ccc;
	background-color: transparent;
	}
	}
	.navbar-default .navbar-link {
	color: #777;
	}
	.navbar-default .navbar-link:hover {
	color: #333;
	}
	.navbar-default .btn-link {
	color: #777;
	}
	.navbar-default .btn-link:hover,
	.navbar-default .btn-link:focus {
	color: #333;
	}
	.navbar-default .btn-link[disabled]:hover,
	fieldset[disabled] .navbar-default .btn-link:hover,
	.navbar-default .btn-link[disabled]:focus,
	fieldset[disabled] .navbar-default .btn-link:focus {
	color: #ccc;
	}
	.navbar-inverse {
	background-color: #222;
	border-color: #080808;
	}
	.navbar-inverse .navbar-brand {
	color: #9d9d9d;
	}
	.navbar-inverse .navbar-brand:hover,
	.navbar-inverse .navbar-brand:focus {
	color: #fff;
	background-color: transparent;
	}
	.navbar-inverse .navbar-text {
	color: #9d9d9d;
	}
	.navbar-inverse .navbar-nav > li > a {
	color: #9d9d9d;
	}
	.navbar-inverse .navbar-nav > li > a:hover,
	.navbar-inverse .navbar-nav > li > a:focus {
	color: #fff;
	background-color: transparent;
	}
	.navbar-inverse .navbar-nav > .active > a,
	.navbar-inverse .navbar-nav > .active > a:hover,
	.navbar-inverse .navbar-nav > .active > a:focus {
	color: #fff;
	background-color: #080808;
	}
	.navbar-inverse .navbar-nav > .disabled > a,
	.navbar-inverse .navbar-nav > .disabled > a:hover,
	.navbar-inverse .navbar-nav > .disabled > a:focus {
	color: #444;
	background-color: transparent;
	}
	.navbar-inverse .navbar-toggle {
	border-color: #333;
	}
	.navbar-inverse .navbar-toggle:hover,
	.navbar-inverse .navbar-toggle:focus {
	background-color: #333;
	}
	.navbar-inverse .navbar-toggle .icon-bar {
	background-color: #fff;
	}
	.navbar-inverse .navbar-collapse,
	.navbar-inverse .navbar-form {
	border-color: #101010;
	}
	.navbar-inverse .navbar-nav > .open > a,
	.navbar-inverse .navbar-nav > .open > a:hover,
	.navbar-inverse .navbar-nav > .open > a:focus {
	background-color: #080808;
	color: #fff;
	}
	@media (max-width: 540px) {
	.navbar-inverse .navbar-nav .open .dropdown-menu > .dropdown-header {
	border-color: #080808;
	}
	.navbar-inverse .navbar-nav .open .dropdown-menu .divider {
	background-color: #080808;
	}
	.navbar-inverse .navbar-nav .open .dropdown-menu > li > a {
	color: #9d9d9d;
	}
	.navbar-inverse .navbar-nav .open .dropdown-menu > li > a:hover,
	.navbar-inverse .navbar-nav .open .dropdown-menu > li > a:focus {
	color: #fff;
	background-color: transparent;
	}
	.navbar-inverse .navbar-nav .open .dropdown-menu > .active > a,
	.navbar-inverse .navbar-nav .open .dropdown-menu > .active > a:hover,
	.navbar-inverse .navbar-nav .open .dropdown-menu > .active > a:focus {
	color: #fff;
	background-color: #080808;
	}
	.navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a,
	.navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a:hover,
	.navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a:focus {
	color: #444;
	background-color: transparent;
	}
	}
	.navbar-inverse .navbar-link {
	color: #9d9d9d;
	}
	.navbar-inverse .navbar-link:hover {
	color: #fff;
	}
	.navbar-inverse .btn-link {
	color: #9d9d9d;
	}
	.navbar-inverse .btn-link:hover,
	.navbar-inverse .btn-link:focus {
	color: #fff;
	}
	.navbar-inverse .btn-link[disabled]:hover,
	fieldset[disabled] .navbar-inverse .btn-link:hover,
	.navbar-inverse .btn-link[disabled]:focus,
	fieldset[disabled] .navbar-inverse .btn-link:focus {
	color: #444;
	}
	.breadcrumb {
	padding: 8px 15px;
	margin-bottom: 18px;
	list-style: none;
	background-color: #f5f5f5;
	border-radius: 2px;
	}
	.breadcrumb > li {
	display: inline-block;
	}
	.breadcrumb > li + li:before {
	content: "/\00a0";
	padding: 0 5px;
	color: #5e5e5e;
	}
	.breadcrumb > .active {
	color: #777777;
	}
	.pagination {
	display: inline-block;
	padding-left: 0;
	margin: 18px 0;
	border-radius: 2px;
	}
	.pagination > li {
	display: inline;
	}
	.pagination > li > a,
	.pagination > li > span {
	position: relative;
	float: left;
	padding: 6px 12px;
	line-height: 1.42857143;
	text-decoration: none;
	color: #337ab7;
	background-color: #fff;
	border: 1px solid #ddd;
	margin-left: -1px;
	}
	.pagination > li:first-child > a,
	.pagination > li:first-child > span {
	margin-left: 0;
	border-bottom-left-radius: 2px;
	border-top-left-radius: 2px;
	}
	.pagination > li:last-child > a,
	.pagination > li:last-child > span {
	border-bottom-right-radius: 2px;
	border-top-right-radius: 2px;
	}
	.pagination > li > a:hover,
	.pagination > li > span:hover,
	.pagination > li > a:focus,
	.pagination > li > span:focus {
	z-index: 2;
	color: #23527c;
	background-color: #eeeeee;
	border-color: #ddd;
	}
	.pagination > .active > a,
	.pagination > .active > span,
	.pagination > .active > a:hover,
	.pagination > .active > span:hover,
	.pagination > .active > a:focus,
	.pagination > .active > span:focus {
	z-index: 3;
	color: #fff;
	background-color: #337ab7;
	border-color: #337ab7;
	cursor: default;
	}
	.pagination > .disabled > span,
	.pagination > .disabled > span:hover,
	.pagination > .disabled > span:focus,
	.pagination > .disabled > a,
	.pagination > .disabled > a:hover,
	.pagination > .disabled > a:focus {
	color: #777777;
	background-color: #fff;
	border-color: #ddd;
	cursor: not-allowed;
	}
	.pagination-lg > li > a,
	.pagination-lg > li > span {
	padding: 10px 16px;
	font-size: 17px;
	line-height: 1.3333333;
	}
	.pagination-lg > li:first-child > a,
	.pagination-lg > li:first-child > span {
	border-bottom-left-radius: 3px;
	border-top-left-radius: 3px;
	}
	.pagination-lg > li:last-child > a,
	.pagination-lg > li:last-child > span {
	border-bottom-right-radius: 3px;
	border-top-right-radius: 3px;
	}
	.pagination-sm > li > a,
	.pagination-sm > li > span {
	padding: 5px 10px;
	font-size: 12px;
	line-height: 1.5;
	}
	.pagination-sm > li:first-child > a,
	.pagination-sm > li:first-child > span {
	border-bottom-left-radius: 1px;
	border-top-left-radius: 1px;
	}
	.pagination-sm > li:last-child > a,
	.pagination-sm > li:last-child > span {
	border-bottom-right-radius: 1px;
	border-top-right-radius: 1px;
	}
	.pager {
	padding-left: 0;
	margin: 18px 0;
	list-style: none;
	text-align: center;
	}
	.pager li {
	display: inline;
	}
	.pager li > a,
	.pager li > span {
	display: inline-block;
	padding: 5px 14px;
	background-color: #fff;
	border: 1px solid #ddd;
	border-radius: 15px;
	}
	.pager li > a:hover,
	.pager li > a:focus {
	text-decoration: none;
	background-color: #eeeeee;
	}
	.pager .next > a,
	.pager .next > span {
	float: right;
	}
	.pager .previous > a,
	.pager .previous > span {
	float: left;
	}
	.pager .disabled > a,
	.pager .disabled > a:hover,
	.pager .disabled > a:focus,
	.pager .disabled > span {
	color: #777777;
	background-color: #fff;
	cursor: not-allowed;
	}
	.label {
	display: inline;
	padding: .2em .6em .3em;
	font-size: 75%;
	font-weight: bold;
	line-height: 1;
	color: #fff;
	text-align: center;
	white-space: nowrap;
	vertical-align: baseline;
	border-radius: .25em;
	}
	a.label:hover,
	a.label:focus {
	color: #fff;
	text-decoration: none;
	cursor: pointer;
	}
	.label:empty {
	display: none;
	}
	.btn .label {
	position: relative;
	top: -1px;
	}
	.label-default {
	background-color: #777777;
	}
	.label-default[href]:hover,
	.label-default[href]:focus {
	background-color: #5e5e5e;
	}
	.label-primary {
	background-color: #337ab7;
	}
	.label-primary[href]:hover,
	.label-primary[href]:focus {
	background-color: #286090;
	}
	.label-success {
	background-color: #5cb85c;
	}
	.label-success[href]:hover,
	.label-success[href]:focus {
	background-color: #449d44;
	}
	.label-info {
	background-color: #5bc0de;
	}
	.label-info[href]:hover,
	.label-info[href]:focus {
	background-color: #31b0d5;
	}
	.label-warning {
	background-color: #f0ad4e;
	}
	.label-warning[href]:hover,
	.label-warning[href]:focus {
	background-color: #ec971f;
	}
	.label-danger {
	background-color: #d9534f;
	}
	.label-danger[href]:hover,
	.label-danger[href]:focus {
	background-color: #c9302c;
	}
	.badge {
	display: inline-block;
	min-width: 10px;
	padding: 3px 7px;
	font-size: 12px;
	font-weight: bold;
	color: #fff;
	line-height: 1;
	vertical-align: middle;
	white-space: nowrap;
	text-align: center;
	background-color: #777777;
	border-radius: 10px;
	}
	.badge:empty {
	display: none;
	}
	.btn .badge {
	position: relative;
	top: -1px;
	}
	.btn-xs .badge,
	.btn-group-xs > .btn .badge {
	top: 0;
	padding: 1px 5px;
	}
	a.badge:hover,
	a.badge:focus {
	color: #fff;
	text-decoration: none;
	cursor: pointer;
	}
	.list-group-item.active > .badge,
	.nav-pills > .active > a > .badge {
	color: #337ab7;
	background-color: #fff;
	}
	.list-group-item > .badge {
	float: right;
	}
	.list-group-item > .badge + .badge {
	margin-right: 5px;
	}
	.nav-pills > li > a > .badge {
	margin-left: 3px;
	}
	.jumbotron {
	padding-top: 30px;
	padding-bottom: 30px;
	margin-bottom: 30px;
	color: inherit;
	background-color: #eeeeee;
	}
	.jumbotron h1,
	.jumbotron .h1 {
	color: inherit;
	}
	.jumbotron p {
	margin-bottom: 15px;
	font-size: 20px;
	font-weight: 200;
	}
	.jumbotron > hr {
	border-top-color: #d5d5d5;
	}
	.container .jumbotron,
	.container-fluid .jumbotron {
	border-radius: 3px;
	padding-left: 0px;
	padding-right: 0px;
	}
	.jumbotron .container {
	max-width: 100%;
	}
	@media screen and (min-width: 768px) {
	.jumbotron {
	padding-top: 48px;
	padding-bottom: 48px;
	}
	.container .jumbotron,
	.container-fluid .jumbotron {
	padding-left: 60px;
	padding-right: 60px;
	}
	.jumbotron h1,
	.jumbotron .h1 {
	font-size: 59px;
	}
	}
	.thumbnail {
	display: block;
	padding: 4px;
	margin-bottom: 18px;
	line-height: 1.42857143;
	background-color: #fff;
	border: 1px solid #ddd;
	border-radius: 2px;
	-webkit-transition: border 0.2s ease-in-out;
	-o-transition: border 0.2s ease-in-out;
	transition: border 0.2s ease-in-out;
	}
	.thumbnail > img,
	.thumbnail a > img {
	margin-left: auto;
	margin-right: auto;
	}
	a.thumbnail:hover,
	a.thumbnail:focus,
	a.thumbnail.active {
	border-color: #337ab7;
	}
	.thumbnail .caption {
	padding: 9px;
	color: #000;
	}
	.alert {
	padding: 15px;
	margin-bottom: 18px;
	border: 1px solid transparent;
	border-radius: 2px;
	}
	.alert h4 {
	margin-top: 0;
	color: inherit;
	}
	.alert .alert-link {
	font-weight: bold;
	}
	.alert > p,
	.alert > ul {
	margin-bottom: 0;
	}
	.alert > p + p {
	margin-top: 5px;
	}
	.alert-dismissable,
	.alert-dismissible {
	padding-right: 35px;
	}
	.alert-dismissable .close,
	.alert-dismissible .close {
	position: relative;
	top: -2px;
	right: -21px;
	color: inherit;
	}
	.alert-success {
	background-color: #dff0d8;
	border-color: #d6e9c6;
	color: #3c763d;
	}
	.alert-success hr {
	border-top-color: #c9e2b3;
	}
	.alert-success .alert-link {
	color: #2b542c;
	}
	.alert-info {
	background-color: #d9edf7;
	border-color: #bce8f1;
	color: #31708f;
	}
	.alert-info hr {
	border-top-color: #a6e1ec;
	}
	.alert-info .alert-link {
	color: #245269;
	}
	.alert-warning {
	background-color: #fcf8e3;
	border-color: #faebcc;
	color: #8a6d3b;
	}
	.alert-warning hr {
	border-top-color: #f7e1b5;
	}
	.alert-warning .alert-link {
	color: #66512c;
	}
	.alert-danger {
	background-color: #f2dede;
	border-color: #ebccd1;
	color: #a94442;
	}
	.alert-danger hr {
	border-top-color: #e4b9c0;
	}
	.alert-danger .alert-link {
	color: #843534;
	}
	@-webkit-keyframes progress-bar-stripes {
	from {
	background-position: 40px 0;
	}
	to {
	background-position: 0 0;
	}
	}
	@keyframes progress-bar-stripes {
	from {
	background-position: 40px 0;
	}
	to {
	background-position: 0 0;
	}
	}
	.progress {
	overflow: hidden;
	height: 18px;
	margin-bottom: 18px;
	background-color: #f5f5f5;
	border-radius: 2px;
	-webkit-box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.1);
	box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.1);
	}
	.progress-bar {
	float: left;
	width: 0%;
	height: 100%;
	font-size: 12px;
	line-height: 18px;
	color: #fff;
	text-align: center;
	background-color: #337ab7;
	-webkit-box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.15);
	box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.15);
	-webkit-transition: width 0.6s ease;
	-o-transition: width 0.6s ease;
	transition: width 0.6s ease;
	}
	.progress-striped .progress-bar,
	.progress-bar-striped {
	background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
	background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
	background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
	background-size: 40px 40px;
	}
	.progress.active .progress-bar,
	.progress-bar.active {
	-webkit-animation: progress-bar-stripes 2s linear infinite;
	-o-animation: progress-bar-stripes 2s linear infinite;
	animation: progress-bar-stripes 2s linear infinite;
	}
	.progress-bar-success {
	background-color: #5cb85c;
	}
	.progress-striped .progress-bar-success {
	background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
	background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
	background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
	}
	.progress-bar-info {
	background-color: #5bc0de;
	}
	.progress-striped .progress-bar-info {
	background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
	background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
	background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
	}
	.progress-bar-warning {
	background-color: #f0ad4e;
	}
	.progress-striped .progress-bar-warning {
	background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
	background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
	background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
	}
	.progress-bar-danger {
	background-color: #d9534f;
	}
	.progress-striped .progress-bar-danger {
	background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
	background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
	background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
	}
	.media {
	margin-top: 15px;
	}
	.media:first-child {
	margin-top: 0;
	}
	.media,
	.media-body {
	zoom: 1;
	overflow: hidden;
	}
	.media-body {
	width: 10000px;
	}
	.media-object {
	display: block;
	}
	.media-object.img-thumbnail {
	max-width: none;
	}
	.media-right,
	.media > .pull-right {
	padding-left: 10px;
	}
	.media-left,
	.media > .pull-left {
	padding-right: 10px;
	}
	.media-left,
	.media-right,
	.media-body {
	display: table-cell;
	vertical-align: top;
	}
	.media-middle {
	vertical-align: middle;
	}
	.media-bottom {
	vertical-align: bottom;
	}
	.media-heading {
	margin-top: 0;
	margin-bottom: 5px;
	}
	.media-list {
	padding-left: 0;
	list-style: none;
	}
	.list-group {
	margin-bottom: 20px;
	padding-left: 0;
	}
	.list-group-item {
	position: relative;
	display: block;
	padding: 10px 15px;
	margin-bottom: -1px;
	background-color: #fff;
	border: 1px solid #ddd;
	}
	.list-group-item:first-child {
	border-top-right-radius: 2px;
	border-top-left-radius: 2px;
	}
	.list-group-item:last-child {
	margin-bottom: 0;
	border-bottom-right-radius: 2px;
	border-bottom-left-radius: 2px;
	}
	a.list-group-item,
	button.list-group-item {
	color: #555;
	}
	a.list-group-item .list-group-item-heading,
	button.list-group-item .list-group-item-heading {
	color: #333;
	}
	a.list-group-item:hover,
	button.list-group-item:hover,
	a.list-group-item:focus,
	button.list-group-item:focus {
	text-decoration: none;
	color: #555;
	background-color: #f5f5f5;
	}
	button.list-group-item {
	width: 100%;
	text-align: left;
	}
	.list-group-item.disabled,
	.list-group-item.disabled:hover,
	.list-group-item.disabled:focus {
	background-color: #eeeeee;
	color: #777777;
	cursor: not-allowed;
	}
	.list-group-item.disabled .list-group-item-heading,
	.list-group-item.disabled:hover .list-group-item-heading,
	.list-group-item.disabled:focus .list-group-item-heading {
	color: inherit;
	}
	.list-group-item.disabled .list-group-item-text,
	.list-group-item.disabled:hover .list-group-item-text,
	.list-group-item.disabled:focus .list-group-item-text {
	color: #777777;
	}
	.list-group-item.active,
	.list-group-item.active:hover,
	.list-group-item.active:focus {
	z-index: 2;
	color: #fff;
	background-color: #337ab7;
	border-color: #337ab7;
	}
	.list-group-item.active .list-group-item-heading,
	.list-group-item.active:hover .list-group-item-heading,
	.list-group-item.active:focus .list-group-item-heading,
	.list-group-item.active .list-group-item-heading > small,
	.list-group-item.active:hover .list-group-item-heading > small,
	.list-group-item.active:focus .list-group-item-heading > small,
	.list-group-item.active .list-group-item-heading > .small,
	.list-group-item.active:hover .list-group-item-heading > .small,
	.list-group-item.active:focus .list-group-item-heading > .small {
	color: inherit;
	}
	.list-group-item.active .list-group-item-text,
	.list-group-item.active:hover .list-group-item-text,
	.list-group-item.active:focus .list-group-item-text {
	color: #c7ddef;
	}
	.list-group-item-success {
	color: #3c763d;
	background-color: #dff0d8;
	}
	a.list-group-item-success,
	button.list-group-item-success {
	color: #3c763d;
	}
	a.list-group-item-success .list-group-item-heading,
	button.list-group-item-success .list-group-item-heading {
	color: inherit;
	}
	a.list-group-item-success:hover,
	button.list-group-item-success:hover,
	a.list-group-item-success:focus,
	button.list-group-item-success:focus {
	color: #3c763d;
	background-color: #d0e9c6;
	}
	a.list-group-item-success.active,
	button.list-group-item-success.active,
	a.list-group-item-success.active:hover,
	button.list-group-item-success.active:hover,
	a.list-group-item-success.active:focus,
	button.list-group-item-success.active:focus {
	color: #fff;
	background-color: #3c763d;
	border-color: #3c763d;
	}
	.list-group-item-info {
	color: #31708f;
	background-color: #d9edf7;
	}
	a.list-group-item-info,
	button.list-group-item-info {
	color: #31708f;
	}
	a.list-group-item-info .list-group-item-heading,
	button.list-group-item-info .list-group-item-heading {
	color: inherit;
	}
	a.list-group-item-info:hover,
	button.list-group-item-info:hover,
	a.list-group-item-info:focus,
	button.list-group-item-info:focus {
	color: #31708f;
	background-color: #c4e3f3;
	}
	a.list-group-item-info.active,
	button.list-group-item-info.active,
	a.list-group-item-info.active:hover,
	button.list-group-item-info.active:hover,
	a.list-group-item-info.active:focus,
	button.list-group-item-info.active:focus {
	color: #fff;
	background-color: #31708f;
	border-color: #31708f;
	}
	.list-group-item-warning {
	color: #8a6d3b;
	background-color: #fcf8e3;
	}
	a.list-group-item-warning,
	button.list-group-item-warning {
	color: #8a6d3b;
	}
	a.list-group-item-warning .list-group-item-heading,
	button.list-group-item-warning .list-group-item-heading {
	color: inherit;
	}
	a.list-group-item-warning:hover,
	button.list-group-item-warning:hover,
	a.list-group-item-warning:focus,
	button.list-group-item-warning:focus {
	color: #8a6d3b;
	background-color: #faf2cc;
	}
	a.list-group-item-warning.active,
	button.list-group-item-warning.active,
	a.list-group-item-warning.active:hover,
	button.list-group-item-warning.active:hover,
	a.list-group-item-warning.active:focus,
	button.list-group-item-warning.active:focus {
	color: #fff;
	background-color: #8a6d3b;
	border-color: #8a6d3b;
	}
	.list-group-item-danger {
	color: #a94442;
	background-color: #f2dede;
	}
	a.list-group-item-danger,
	button.list-group-item-danger {
	color: #a94442;
	}
	a.list-group-item-danger .list-group-item-heading,
	button.list-group-item-danger .list-group-item-heading {
	color: inherit;
	}
	a.list-group-item-danger:hover,
	button.list-group-item-danger:hover,
	a.list-group-item-danger:focus,
	button.list-group-item-danger:focus {
	color: #a94442;
	background-color: #ebcccc;
	}
	a.list-group-item-danger.active,
	button.list-group-item-danger.active,
	a.list-group-item-danger.active:hover,
	button.list-group-item-danger.active:hover,
	a.list-group-item-danger.active:focus,
	button.list-group-item-danger.active:focus {
	color: #fff;
	background-color: #a94442;
	border-color: #a94442;
	}
	.list-group-item-heading {
	margin-top: 0;
	margin-bottom: 5px;
	}
	.list-group-item-text {
	margin-bottom: 0;
	line-height: 1.3;
	}
	.panel {
	margin-bottom: 18px;
	background-color: #fff;
	border: 1px solid transparent;
	border-radius: 2px;
	-webkit-box-shadow: 0 1px 1px rgba(0, 0, 0, 0.05);
	box-shadow: 0 1px 1px rgba(0, 0, 0, 0.05);
	}
	.panel-body {
	padding: 15px;
	}
	.panel-heading {
	padding: 10px 15px;
	border-bottom: 1px solid transparent;
	border-top-right-radius: 1px;
	border-top-left-radius: 1px;
	}
	.panel-heading > .dropdown .dropdown-toggle {
	color: inherit;
	}
	.panel-title {
	margin-top: 0;
	margin-bottom: 0;
	font-size: 15px;
	color: inherit;
	}
	.panel-title > a,
	.panel-title > small,
	.panel-title > .small,
	.panel-title > small > a,
	.panel-title > .small > a {
	color: inherit;
	}
	.panel-footer {
	padding: 10px 15px;
	background-color: #f5f5f5;
	border-top: 1px solid #ddd;
	border-bottom-right-radius: 1px;
	border-bottom-left-radius: 1px;
	}
	.panel > .list-group,
	.panel > .panel-collapse > .list-group {
	margin-bottom: 0;
	}
	.panel > .list-group .list-group-item,
	.panel > .panel-collapse > .list-group .list-group-item {
	border-width: 1px 0;
	border-radius: 0;
	}
	.panel > .list-group:first-child .list-group-item:first-child,
	.panel > .panel-collapse > .list-group:first-child .list-group-item:first-child {
	border-top: 0;
	border-top-right-radius: 1px;
	border-top-left-radius: 1px;
	}
	.panel > .list-group:last-child .list-group-item:last-child,
	.panel > .panel-collapse > .list-group:last-child .list-group-item:last-child {
	border-bottom: 0;
	border-bottom-right-radius: 1px;
	border-bottom-left-radius: 1px;
	}
	.panel > .panel-heading + .panel-collapse > .list-group .list-group-item:first-child {
	border-top-right-radius: 0;
	border-top-left-radius: 0;
	}
	.panel-heading + .list-group .list-group-item:first-child {
	border-top-width: 0;
	}
	.list-group + .panel-footer {
	border-top-width: 0;
	}
	.panel > .table,
	.panel > .table-responsive > .table,
	.panel > .panel-collapse > .table {
	margin-bottom: 0;
	}
	.panel > .table caption,
	.panel > .table-responsive > .table caption,
	.panel > .panel-collapse > .table caption {
	padding-left: 15px;
	padding-right: 15px;
	}
	.panel > .table:first-child,
	.panel > .table-responsive:first-child > .table:first-child {
	border-top-right-radius: 1px;
	border-top-left-radius: 1px;
	}
	.panel > .table:first-child > thead:first-child > tr:first-child,
	.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child,
	.panel > .table:first-child > tbody:first-child > tr:first-child,
	.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child {
	border-top-left-radius: 1px;
	border-top-right-radius: 1px;
	}
	.panel > .table:first-child > thead:first-child > tr:first-child td:first-child,
	.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child td:first-child,
	.panel > .table:first-child > tbody:first-child > tr:first-child td:first-child,
	.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child td:first-child,
	.panel > .table:first-child > thead:first-child > tr:first-child th:first-child,
	.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child th:first-child,
	.panel > .table:first-child > tbody:first-child > tr:first-child th:first-child,
	.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child th:first-child {
	border-top-left-radius: 1px;
	}
	.panel > .table:first-child > thead:first-child > tr:first-child td:last-child,
	.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child td:last-child,
	.panel > .table:first-child > tbody:first-child > tr:first-child td:last-child,
	.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child td:last-child,
	.panel > .table:first-child > thead:first-child > tr:first-child th:last-child,
	.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child th:last-child,
	.panel > .table:first-child > tbody:first-child > tr:first-child th:last-child,
	.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child th:last-child {
	border-top-right-radius: 1px;
	}
	.panel > .table:last-child,
	.panel > .table-responsive:last-child > .table:last-child {
	border-bottom-right-radius: 1px;
	border-bottom-left-radius: 1px;
	}
	.panel > .table:last-child > tbody:last-child > tr:last-child,
	.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child,
	.panel > .table:last-child > tfoot:last-child > tr:last-child,
	.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child {
	border-bottom-left-radius: 1px;
	border-bottom-right-radius: 1px;
	}
	.panel > .table:last-child > tbody:last-child > tr:last-child td:first-child,
	.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child td:first-child,
	.panel > .table:last-child > tfoot:last-child > tr:last-child td:first-child,
	.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child td:first-child,
	.panel > .table:last-child > tbody:last-child > tr:last-child th:first-child,
	.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child th:first-child,
	.panel > .table:last-child > tfoot:last-child > tr:last-child th:first-child,
	.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child th:first-child {
	border-bottom-left-radius: 1px;
	}
	.panel > .table:last-child > tbody:last-child > tr:last-child td:last-child,
	.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child td:last-child,
	.panel > .table:last-child > tfoot:last-child > tr:last-child td:last-child,
	.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child td:last-child,
	.panel > .table:last-child > tbody:last-child > tr:last-child th:last-child,
	.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child th:last-child,
	.panel > .table:last-child > tfoot:last-child > tr:last-child th:last-child,
	.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child th:last-child {
	border-bottom-right-radius: 1px;
	}
	.panel > .panel-body + .table,
	.panel > .panel-body + .table-responsive,
	.panel > .table + .panel-body,
	.panel > .table-responsive + .panel-body {
	border-top: 1px solid #ddd;
	}
	.panel > .table > tbody:first-child > tr:first-child th,
	.panel > .table > tbody:first-child > tr:first-child td {
	border-top: 0;
	}
	.panel > .table-bordered,
	.panel > .table-responsive > .table-bordered {
	border: 0;
	}
	.panel > .table-bordered > thead > tr > th:first-child,
	.panel > .table-responsive > .table-bordered > thead > tr > th:first-child,
	.panel > .table-bordered > tbody > tr > th:first-child,
	.panel > .table-responsive > .table-bordered > tbody > tr > th:first-child,
	.panel > .table-bordered > tfoot > tr > th:first-child,
	.panel > .table-responsive > .table-bordered > tfoot > tr > th:first-child,
	.panel > .table-bordered > thead > tr > td:first-child,
	.panel > .table-responsive > .table-bordered > thead > tr > td:first-child,
	.panel > .table-bordered > tbody > tr > td:first-child,
	.panel > .table-responsive > .table-bordered > tbody > tr > td:first-child,
	.panel > .table-bordered > tfoot > tr > td:first-child,
	.panel > .table-responsive > .table-bordered > tfoot > tr > td:first-child {
	border-left: 0;
	}
	.panel > .table-bordered > thead > tr > th:last-child,
	.panel > .table-responsive > .table-bordered > thead > tr > th:last-child,
	.panel > .table-bordered > tbody > tr > th:last-child,
	.panel > .table-responsive > .table-bordered > tbody > tr > th:last-child,
	.panel > .table-bordered > tfoot > tr > th:last-child,
	.panel > .table-responsive > .table-bordered > tfoot > tr > th:last-child,
	.panel > .table-bordered > thead > tr > td:last-child,
	.panel > .table-responsive > .table-bordered > thead > tr > td:last-child,
	.panel > .table-bordered > tbody > tr > td:last-child,
	.panel > .table-responsive > .table-bordered > tbody > tr > td:last-child,
	.panel > .table-bordered > tfoot > tr > td:last-child,
	.panel > .table-responsive > .table-bordered > tfoot > tr > td:last-child {
	border-right: 0;
	}
	.panel > .table-bordered > thead > tr:first-child > td,
	.panel > .table-responsive > .table-bordered > thead > tr:first-child > td,
	.panel > .table-bordered > tbody > tr:first-child > td,
	.panel > .table-responsive > .table-bordered > tbody > tr:first-child > td,
	.panel > .table-bordered > thead > tr:first-child > th,
	.panel > .table-responsive > .table-bordered > thead > tr:first-child > th,
	.panel > .table-bordered > tbody > tr:first-child > th,
	.panel > .table-responsive > .table-bordered > tbody > tr:first-child > th {
	border-bottom: 0;
	}
	.panel > .table-bordered > tbody > tr:last-child > td,
	.panel > .table-responsive > .table-bordered > tbody > tr:last-child > td,
	.panel > .table-bordered > tfoot > tr:last-child > td,
	.panel > .table-responsive > .table-bordered > tfoot > tr:last-child > td,
	.panel > .table-bordered > tbody > tr:last-child > th,
	.panel > .table-responsive > .table-bordered > tbody > tr:last-child > th,
	.panel > .table-bordered > tfoot > tr:last-child > th,
	.panel > .table-responsive > .table-bordered > tfoot > tr:last-child > th {
	border-bottom: 0;
	}
	.panel > .table-responsive {
	border: 0;
	margin-bottom: 0;
	}
	.panel-group {
	margin-bottom: 18px;
	}
	.panel-group .panel {
	margin-bottom: 0;
	border-radius: 2px;
	}
	.panel-group .panel + .panel {
	margin-top: 5px;
	}
	.panel-group .panel-heading {
	border-bottom: 0;
	}
	.panel-group .panel-heading + .panel-collapse > .panel-body,
	.panel-group .panel-heading + .panel-collapse > .list-group {
	border-top: 1px solid #ddd;
	}
	.panel-group .panel-footer {
	border-top: 0;
	}
	.panel-group .panel-footer + .panel-collapse .panel-body {
	border-bottom: 1px solid #ddd;
	}
	.panel-default {
	border-color: #ddd;
	}
	.panel-default > .panel-heading {
	color: #333333;
	background-color: #f5f5f5;
	border-color: #ddd;
	}
	.panel-default > .panel-heading + .panel-collapse > .panel-body {
	border-top-color: #ddd;
	}
	.panel-default > .panel-heading .badge {
	color: #f5f5f5;
	background-color: #333333;
	}
	.panel-default > .panel-footer + .panel-collapse > .panel-body {
	border-bottom-color: #ddd;
	}
	.panel-primary {
	border-color: #337ab7;
	}
	.panel-primary > .panel-heading {
	color: #fff;
	background-color: #337ab7;
	border-color: #337ab7;
	}
	.panel-primary > .panel-heading + .panel-collapse > .panel-body {
	border-top-color: #337ab7;
	}
	.panel-primary > .panel-heading .badge {
	color: #337ab7;
	background-color: #fff;
	}
	.panel-primary > .panel-footer + .panel-collapse > .panel-body {
	border-bottom-color: #337ab7;
	}
	.panel-success {
	border-color: #d6e9c6;
	}
	.panel-success > .panel-heading {
	color: #3c763d;
	background-color: #dff0d8;
	border-color: #d6e9c6;
	}
	.panel-success > .panel-heading + .panel-collapse > .panel-body {
	border-top-color: #d6e9c6;
	}
	.panel-success > .panel-heading .badge {
	color: #dff0d8;
	background-color: #3c763d;
	}
	.panel-success > .panel-footer + .panel-collapse > .panel-body {
	border-bottom-color: #d6e9c6;
	}
	.panel-info {
	border-color: #bce8f1;
	}
	.panel-info > .panel-heading {
	color: #31708f;
	background-color: #d9edf7;
	border-color: #bce8f1;
	}
	.panel-info > .panel-heading + .panel-collapse > .panel-body {
	border-top-color: #bce8f1;
	}
	.panel-info > .panel-heading .badge {
	color: #d9edf7;
	background-color: #31708f;
	}
	.panel-info > .panel-footer + .panel-collapse > .panel-body {
	border-bottom-color: #bce8f1;
	}
	.panel-warning {
	border-color: #faebcc;
	}
	.panel-warning > .panel-heading {
	color: #8a6d3b;
	background-color: #fcf8e3;
	border-color: #faebcc;
	}
	.panel-warning > .panel-heading + .panel-collapse > .panel-body {
	border-top-color: #faebcc;
	}
	.panel-warning > .panel-heading .badge {
	color: #fcf8e3;
	background-color: #8a6d3b;
	}
	.panel-warning > .panel-footer + .panel-collapse > .panel-body {
	border-bottom-color: #faebcc;
	}
	.panel-danger {
	border-color: #ebccd1;
	}
	.panel-danger > .panel-heading {
	color: #a94442;
	background-color: #f2dede;
	border-color: #ebccd1;
	}
	.panel-danger > .panel-heading + .panel-collapse > .panel-body {
	border-top-color: #ebccd1;
	}
	.panel-danger > .panel-heading .badge {
	color: #f2dede;
	background-color: #a94442;
	}
	.panel-danger > .panel-footer + .panel-collapse > .panel-body {
	border-bottom-color: #ebccd1;
	}
	.embed-responsive {
	position: relative;
	display: block;
	height: 0;
	padding: 0;
	overflow: hidden;
	}
	.embed-responsive .embed-responsive-item,
	.embed-responsive iframe,
	.embed-responsive embed,
	.embed-responsive object,
	.embed-responsive video {
	position: absolute;
	top: 0;
	left: 0;
	bottom: 0;
	height: 100%;
	width: 100%;
	border: 0;
	}
	.embed-responsive-16by9 {
	padding-bottom: 56.25%;
	}
	.embed-responsive-4by3 {
	padding-bottom: 75%;
	}
	.well {
	min-height: 20px;
	padding: 19px;
	margin-bottom: 20px;
	background-color: #f5f5f5;
	border: 1px solid #e3e3e3;
	border-radius: 2px;
	-webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.05);
	box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.05);
	}
	.well blockquote {
	border-color: #ddd;
	border-color: rgba(0, 0, 0, 0.15);
	}
	.well-lg {
	padding: 24px;
	border-radius: 3px;
	}
	.well-sm {
	padding: 9px;
	border-radius: 1px;
	}
	.close {
	float: right;
	font-size: 19.5px;
	font-weight: bold;
	line-height: 1;
	color: #000;
	text-shadow: 0 1px 0 #fff;
	opacity: 0.2;
	filter: alpha(opacity=20);
	}
	.close:hover,
	.close:focus {
	color: #000;
	text-decoration: none;
	cursor: pointer;
	opacity: 0.5;
	filter: alpha(opacity=50);
	}
	button.close {
	padding: 0;
	cursor: pointer;
	background: transparent;
	border: 0;
	-webkit-appearance: none;
	}
	.modal-open {
	overflow: hidden;
	}
	.modal {
	display: none;
	overflow: hidden;
	position: fixed;
	top: 0;
	right: 0;
	bottom: 0;
	left: 0;
	z-index: 1050;
	-webkit-overflow-scrolling: touch;
	outline: 0;
	}
	.modal.fade .modal-dialog {
	-webkit-transform: translate(0, -25%);
	-ms-transform: translate(0, -25%);
	-o-transform: translate(0, -25%);
	transform: translate(0, -25%);
	-webkit-transition: -webkit-transform 0.3s ease-out;
	-moz-transition: -moz-transform 0.3s ease-out;
	-o-transition: -o-transform 0.3s ease-out;
	transition: transform 0.3s ease-out;
	}
	.modal.in .modal-dialog {
	-webkit-transform: translate(0, 0);
	-ms-transform: translate(0, 0);
	-o-transform: translate(0, 0);
	transform: translate(0, 0);
	}
	.modal-open .modal {
	overflow-x: hidden;
	overflow-y: auto;
	}
	.modal-dialog {
	position: relative;
	width: auto;
	margin: 10px;
	}
	.modal-content {
	position: relative;
	background-color: #fff;
	border: 1px solid #999;
	border: 1px solid rgba(0, 0, 0, 0.2);
	border-radius: 3px;
	-webkit-box-shadow: 0 3px 9px rgba(0, 0, 0, 0.5);
	box-shadow: 0 3px 9px rgba(0, 0, 0, 0.5);
	background-clip: padding-box;
	outline: 0;
	}
	.modal-backdrop {
	position: fixed;
	top: 0;
	right: 0;
	bottom: 0;
	left: 0;
	z-index: 1040;
	background-color: #000;
	}
	.modal-backdrop.fade {
	opacity: 0;
	filter: alpha(opacity=0);
	}
	.modal-backdrop.in {
	opacity: 0.5;
	filter: alpha(opacity=50);
	}
	.modal-header {
	padding: 15px;
	border-bottom: 1px solid #e5e5e5;
	}
	.modal-header .close {
	margin-top: -2px;
	}
	.modal-title {
	margin: 0;
	line-height: 1.42857143;
	}
	.modal-body {
	position: relative;
	padding: 15px;
	}
	.modal-footer {
	padding: 15px;
	text-align: right;
	border-top: 1px solid #e5e5e5;
	}
	.modal-footer .btn + .btn {
	margin-left: 5px;
	margin-bottom: 0;
	}
	.modal-footer .btn-group .btn + .btn {
	margin-left: -1px;
	}
	.modal-footer .btn-block + .btn-block {
	margin-left: 0;
	}
	.modal-scrollbar-measure {
	position: absolute;
	top: -9999px;
	width: 50px;
	height: 50px;
	overflow: scroll;
	}
	@media (min-width: 768px) {
	.modal-dialog {
	width: 600px;
	margin: 30px auto;
	}
	.modal-content {
	-webkit-box-shadow: 0 5px 15px rgba(0, 0, 0, 0.5);
	box-shadow: 0 5px 15px rgba(0, 0, 0, 0.5);
	}
	.modal-sm {
	width: 300px;
	}
	}
	@media (min-width: 992px) {
	.modal-lg {
	width: 900px;
	}
	}
	.tooltip {
	position: absolute;
	z-index: 1070;
	display: block;
	font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
	font-style: normal;
	font-weight: normal;
	letter-spacing: normal;
	line-break: auto;
	line-height: 1.42857143;
	text-align: left;
	text-align: start;
	text-decoration: none;
	text-shadow: none;
	text-transform: none;
	white-space: normal;
	word-break: normal;
	word-spacing: normal;
	word-wrap: normal;
	font-size: 12px;
	opacity: 0;
	filter: alpha(opacity=0);
	}
	.tooltip.in {
	opacity: 0.9;
	filter: alpha(opacity=90);
	}
	.tooltip.top {
	margin-top: -3px;
	padding: 5px 0;
	}
	.tooltip.right {
	margin-left: 3px;
	padding: 0 5px;
	}
	.tooltip.bottom {
	margin-top: 3px;
	padding: 5px 0;
	}
	.tooltip.left {
	margin-left: -3px;
	padding: 0 5px;
	}
	.tooltip-inner {
	max-width: 200px;
	padding: 3px 8px;
	color: #fff;
	text-align: center;
	background-color: #000;
	border-radius: 2px;
	}
	.tooltip-arrow {
	position: absolute;
	width: 0;
	height: 0;
	border-color: transparent;
	border-style: solid;
	}
	.tooltip.top .tooltip-arrow {
	bottom: 0;
	left: 50%;
	margin-left: -5px;
	border-width: 5px 5px 0;
	border-top-color: #000;
	}
	.tooltip.top-left .tooltip-arrow {
	bottom: 0;
	right: 5px;
	margin-bottom: -5px;
	border-width: 5px 5px 0;
	border-top-color: #000;
	}
	.tooltip.top-right .tooltip-arrow {
	bottom: 0;
	left: 5px;
	margin-bottom: -5px;
	border-width: 5px 5px 0;
	border-top-color: #000;
	}
	.tooltip.right .tooltip-arrow {
	top: 50%;
	left: 0;
	margin-top: -5px;
	border-width: 5px 5px 5px 0;
	border-right-color: #000;
	}
	.tooltip.left .tooltip-arrow {
	top: 50%;
	right: 0;
	margin-top: -5px;
	border-width: 5px 0 5px 5px;
	border-left-color: #000;
	}
	.tooltip.bottom .tooltip-arrow {
	top: 0;
	left: 50%;
	margin-left: -5px;
	border-width: 0 5px 5px;
	border-bottom-color: #000;
	}
	.tooltip.bottom-left .tooltip-arrow {
	top: 0;
	right: 5px;
	margin-top: -5px;
	border-width: 0 5px 5px;
	border-bottom-color: #000;
	}
	.tooltip.bottom-right .tooltip-arrow {
	top: 0;
	left: 5px;
	margin-top: -5px;
	border-width: 0 5px 5px;
	border-bottom-color: #000;
	}
	.popover {
	position: absolute;
	top: 0;
	left: 0;
	z-index: 1060;
	display: none;
	max-width: 276px;
	padding: 1px;
	font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
	font-style: normal;
	font-weight: normal;
	letter-spacing: normal;
	line-break: auto;
	line-height: 1.42857143;
	text-align: left;
	text-align: start;
	text-decoration: none;
	text-shadow: none;
	text-transform: none;
	white-space: normal;
	word-break: normal;
	word-spacing: normal;
	word-wrap: normal;
	font-size: 13px;
	background-color: #fff;
	background-clip: padding-box;
	border: 1px solid #ccc;
	border: 1px solid rgba(0, 0, 0, 0.2);
	border-radius: 3px;
	-webkit-box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2);
	box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2);
	}
	.popover.top {
	margin-top: -10px;
	}
	.popover.right {
	margin-left: 10px;
	}
	.popover.bottom {
	margin-top: 10px;
	}
	.popover.left {
	margin-left: -10px;
	}
	.popover-title {
	margin: 0;
	padding: 8px 14px;
	font-size: 13px;
	background-color: #f7f7f7;
	border-bottom: 1px solid #ebebeb;
	border-radius: 2px 2px 0 0;
	}
	.popover-content {
	padding: 9px 14px;
	}
	.popover > .arrow,
	.popover > .arrow:after {
	position: absolute;
	display: block;
	width: 0;
	height: 0;
	border-color: transparent;
	border-style: solid;
	}
	.popover > .arrow {
	border-width: 11px;
	}
	.popover > .arrow:after {
	border-width: 10px;
	content: "";
	}
	.popover.top > .arrow {
	left: 50%;
	margin-left: -11px;
	border-bottom-width: 0;
	border-top-color: #999999;
	border-top-color: rgba(0, 0, 0, 0.25);
	bottom: -11px;
	}
	.popover.top > .arrow:after {
	content: " ";
	bottom: 1px;
	margin-left: -10px;
	border-bottom-width: 0;
	border-top-color: #fff;
	}
	.popover.right > .arrow {
	top: 50%;
	left: -11px;
	margin-top: -11px;
	border-left-width: 0;
	border-right-color: #999999;
	border-right-color: rgba(0, 0, 0, 0.25);
	}
	.popover.right > .arrow:after {
	content: " ";
	left: 1px;
	bottom: -10px;
	border-left-width: 0;
	border-right-color: #fff;
	}
	.popover.bottom > .arrow {
	left: 50%;
	margin-left: -11px;
	border-top-width: 0;
	border-bottom-color: #999999;
	border-bottom-color: rgba(0, 0, 0, 0.25);
	top: -11px;
	}
	.popover.bottom > .arrow:after {
	content: " ";
	top: 1px;
	margin-left: -10px;
	border-top-width: 0;
	border-bottom-color: #fff;
	}
	.popover.left > .arrow {
	top: 50%;
	right: -11px;
	margin-top: -11px;
	border-right-width: 0;
	border-left-color: #999999;
	border-left-color: rgba(0, 0, 0, 0.25);
	}
	.popover.left > .arrow:after {
	content: " ";
	right: 1px;
	border-right-width: 0;
	border-left-color: #fff;
	bottom: -10px;
	}
	.carousel {
	position: relative;
	}
	.carousel-inner {
	position: relative;
	overflow: hidden;
	width: 100%;
	}
	.carousel-inner > .item {
	display: none;
	position: relative;
	-webkit-transition: 0.6s ease-in-out left;
	-o-transition: 0.6s ease-in-out left;
	transition: 0.6s ease-in-out left;
	}
	.carousel-inner > .item > img,
	.carousel-inner > .item > a > img {
	line-height: 1;
	}
	@media all and (transform-3d), (-webkit-transform-3d) {
	.carousel-inner > .item {
	-webkit-transition: -webkit-transform 0.6s ease-in-out;
	-moz-transition: -moz-transform 0.6s ease-in-out;
	-o-transition: -o-transform 0.6s ease-in-out;
	transition: transform 0.6s ease-in-out;
	-webkit-backface-visibility: hidden;
	-moz-backface-visibility: hidden;
	backface-visibility: hidden;
	-webkit-perspective: 1000px;
	-moz-perspective: 1000px;
	perspective: 1000px;
	}
	.carousel-inner > .item.next,
	.carousel-inner > .item.active.right {
	-webkit-transform: translate3d(100%, 0, 0);
	transform: translate3d(100%, 0, 0);
	left: 0;
	}
	.carousel-inner > .item.prev,
	.carousel-inner > .item.active.left {
	-webkit-transform: translate3d(-100%, 0, 0);
	transform: translate3d(-100%, 0, 0);
	left: 0;
	}
	.carousel-inner > .item.next.left,
	.carousel-inner > .item.prev.right,
	.carousel-inner > .item.active {
	-webkit-transform: translate3d(0, 0, 0);
	transform: translate3d(0, 0, 0);
	left: 0;
	}
	}
	.carousel-inner > .active,
	.carousel-inner > .next,
	.carousel-inner > .prev {
	display: block;
	}
	.carousel-inner > .active {
	left: 0;
	}
	.carousel-inner > .next,
	.carousel-inner > .prev {
	position: absolute;
	top: 0;
	width: 100%;
	}
	.carousel-inner > .next {
	left: 100%;
	}
	.carousel-inner > .prev {
	left: -100%;
	}
	.carousel-inner > .next.left,
	.carousel-inner > .prev.right {
	left: 0;
	}
	.carousel-inner > .active.left {
	left: -100%;
	}
	.carousel-inner > .active.right {
	left: 100%;
	}
	.carousel-control {
	position: absolute;
	top: 0;
	left: 0;
	bottom: 0;
	width: 15%;
	opacity: 0.5;
	filter: alpha(opacity=50);
	font-size: 20px;
	color: #fff;
	text-align: center;
	text-shadow: 0 1px 2px rgba(0, 0, 0, 0.6);
	background-color: rgba(0, 0, 0, 0);
	}
	.carousel-control.left {
	background-image: -webkit-linear-gradient(left, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
	background-image: -o-linear-gradient(left, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
	background-image: linear-gradient(to right, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
	background-repeat: repeat-x;
	filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#80000000', endColorstr='#00000000', GradientType=1);
	}
	.carousel-control.right {
	left: auto;
	right: 0;
	background-image: -webkit-linear-gradient(left, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
	background-image: -o-linear-gradient(left, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
	background-image: linear-gradient(to right, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
	background-repeat: repeat-x;
	filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#00000000', endColorstr='#80000000', GradientType=1);
	}
	.carousel-control:hover,
	.carousel-control:focus {
	outline: 0;
	color: #fff;
	text-decoration: none;
	opacity: 0.9;
	filter: alpha(opacity=90);
	}
	.carousel-control .icon-prev,
	.carousel-control .icon-next,
	.carousel-control .glyphicon-chevron-left,
	.carousel-control .glyphicon-chevron-right {
	position: absolute;
	top: 50%;
	margin-top: -10px;
	z-index: 5;
	display: inline-block;
	}
	.carousel-control .icon-prev,
	.carousel-control .glyphicon-chevron-left {
	left: 50%;
	margin-left: -10px;
	}
	.carousel-control .icon-next,
	.carousel-control .glyphicon-chevron-right {
	right: 50%;
	margin-right: -10px;
	}
	.carousel-control .icon-prev,
	.carousel-control .icon-next {
	width: 20px;
	height: 20px;
	line-height: 1;
	font-family: serif;
	}
	.carousel-control .icon-prev:before {
	content: '\2039';
	}
	.carousel-control .icon-next:before {
	content: '\203a';
	}
	.carousel-indicators {
	position: absolute;
	bottom: 10px;
	left: 50%;
	z-index: 15;
	width: 60%;
	margin-left: -30%;
	padding-left: 0;
	list-style: none;
	text-align: center;
	}
	.carousel-indicators li {
	display: inline-block;
	width: 10px;
	height: 10px;
	margin: 1px;
	text-indent: -999px;
	border: 1px solid #fff;
	border-radius: 10px;
	cursor: pointer;
	background-color: #000 \9;
	background-color: rgba(0, 0, 0, 0);
	}
	.carousel-indicators .active {
	margin: 0;
	width: 12px;
	height: 12px;
	background-color: #fff;
	}
	.carousel-caption {
	position: absolute;
	left: 15%;
	right: 15%;
	bottom: 20px;
	z-index: 10;
	padding-top: 20px;
	padding-bottom: 20px;
	color: #fff;
	text-align: center;
	text-shadow: 0 1px 2px rgba(0, 0, 0, 0.6);
	}
	.carousel-caption .btn {
	text-shadow: none;
	}
	@media screen and (min-width: 768px) {
	.carousel-control .glyphicon-chevron-left,
	.carousel-control .glyphicon-chevron-right,
	.carousel-control .icon-prev,
	.carousel-control .icon-next {
	width: 30px;
	height: 30px;
	margin-top: -10px;
	font-size: 30px;
	}
	.carousel-control .glyphicon-chevron-left,
	.carousel-control .icon-prev {
	margin-left: -10px;
	}
	.carousel-control .glyphicon-chevron-right,
	.carousel-control .icon-next {
	margin-right: -10px;
	}
	.carousel-caption {
	left: 20%;
	right: 20%;
	padding-bottom: 30px;
	}
	.carousel-indicators {
	bottom: 20px;
	}
	}
	.clearfix:before,
	.clearfix:after,
	.dl-horizontal dd:before,
	.dl-horizontal dd:after,
	.container:before,
	.container:after,
	.container-fluid:before,
	.container-fluid:after,
	.row:before,
	.row:after,
	.form-horizontal .form-group:before,
	.form-horizontal .form-group:after,
	.btn-toolbar:before,
	.btn-toolbar:after,
	.btn-group-vertical > .btn-group:before,
	.btn-group-vertical > .btn-group:after,
	.nav:before,
	.nav:after,
	.navbar:before,
	.navbar:after,
	.navbar-header:before,
	.navbar-header:after,
	.navbar-collapse:before,
	.navbar-collapse:after,
	.pager:before,
	.pager:after,
	.panel-body:before,
	.panel-body:after,
	.modal-header:before,
	.modal-header:after,
	.modal-footer:before,
	.modal-footer:after,
	.item_buttons:before,
	.item_buttons:after {
	content: " ";
	display: table;
	}
	.clearfix:after,
	.dl-horizontal dd:after,
	.container:after,
	.container-fluid:after,
	.row:after,
	.form-horizontal .form-group:after,
	.btn-toolbar:after,
	.btn-group-vertical > .btn-group:after,
	.nav:after,
	.navbar:after,
	.navbar-header:after,
	.navbar-collapse:after,
	.pager:after,
	.panel-body:after,
	.modal-header:after,
	.modal-footer:after,
	.item_buttons:after {
	clear: both;
	}
	.center-block {
	display: block;
	margin-left: auto;
	margin-right: auto;
	}
	.pull-right {
	float: right !important;
	}
	.pull-left {
	float: left !important;
	}
	.hide {
	display: none !important;
	}
	.show {
	display: block !important;
	}
	.invisible {
	visibility: hidden;
	}
	.text-hide {
	font: 0/0 a;
	color: transparent;
	text-shadow: none;
	background-color: transparent;
	border: 0;
	}
	.hidden {
	display: none !important;
	}
	.affix {
	position: fixed;
	}
	@-ms-viewport {
	width: device-width;
	}
	.visible-xs,
	.visible-sm,
	.visible-md,
	.visible-lg {
	display: none !important;
	}
	.visible-xs-block,
	.visible-xs-inline,
	.visible-xs-inline-block,
	.visible-sm-block,
	.visible-sm-inline,
	.visible-sm-inline-block,
	.visible-md-block,
	.visible-md-inline,
	.visible-md-inline-block,
	.visible-lg-block,
	.visible-lg-inline,
	.visible-lg-inline-block {
	display: none !important;
	}
	@media (max-width: 767px) {
	.visible-xs {
	display: block !important;
	}
	table.visible-xs {
	display: table !important;
	}
	tr.visible-xs {
	display: table-row !important;
	}
	th.visible-xs,
	td.visible-xs {
	display: table-cell !important;
	}
	}
	@media (max-width: 767px) {
	.visible-xs-block {
	display: block !important;
	}
	}
	@media (max-width: 767px) {
	.visible-xs-inline {
	display: inline !important;
	}
	}
	@media (max-width: 767px) {
	.visible-xs-inline-block {
	display: inline-block !important;
	}
	}
	@media (min-width: 768px) and (max-width: 991px) {
	.visible-sm {
	display: block !important;
	}
	table.visible-sm {
	display: table !important;
	}
	tr.visible-sm {
	display: table-row !important;
	}
	th.visible-sm,
	td.visible-sm {
	display: table-cell !important;
	}
	}
	@media (min-width: 768px) and (max-width: 991px) {
	.visible-sm-block {
	display: block !important;
	}
	}
	@media (min-width: 768px) and (max-width: 991px) {
	.visible-sm-inline {
	display: inline !important;
	}
	}
	@media (min-width: 768px) and (max-width: 991px) {
	.visible-sm-inline-block {
	display: inline-block !important;
	}
	}
	@media (min-width: 992px) and (max-width: 1199px) {
	.visible-md {
	display: block !important;
	}
	table.visible-md {
	display: table !important;
	}
	tr.visible-md {
	display: table-row !important;
	}
	th.visible-md,
	td.visible-md {
	display: table-cell !important;
	}
	}
	@media (min-width: 992px) and (max-width: 1199px) {
	.visible-md-block {
	display: block !important;
	}
	}
	@media (min-width: 992px) and (max-width: 1199px) {
	.visible-md-inline {
	display: inline !important;
	}
	}
	@media (min-width: 992px) and (max-width: 1199px) {
	.visible-md-inline-block {
	display: inline-block !important;
	}
	}
	@media (min-width: 1200px) {
	.visible-lg {
	display: block !important;
	}
	table.visible-lg {
	display: table !important;
	}
	tr.visible-lg {
	display: table-row !important;
	}
	th.visible-lg,
	td.visible-lg {
	display: table-cell !important;
	}
	}
	@media (min-width: 1200px) {
	.visible-lg-block {
	display: block !important;
	}
	}
	@media (min-width: 1200px) {
	.visible-lg-inline {
	display: inline !important;
	}
	}
	@media (min-width: 1200px) {
	.visible-lg-inline-block {
	display: inline-block !important;
	}
	}
	@media (max-width: 767px) {
	.hidden-xs {
	display: none !important;
	}
	}
	@media (min-width: 768px) and (max-width: 991px) {
	.hidden-sm {
	display: none !important;
	}
	}
	@media (min-width: 992px) and (max-width: 1199px) {
	.hidden-md {
	display: none !important;
	}
	}
	@media (min-width: 1200px) {
	.hidden-lg {
	display: none !important;
	}
	}
	.visible-print {
	display: none !important;
	}
	@media print {
	.visible-print {
	display: block !important;
	}
	table.visible-print {
	display: table !important;
	}
	tr.visible-print {
	display: table-row !important;
	}
	th.visible-print,
	td.visible-print {
	display: table-cell !important;
	}
	}
	.visible-print-block {
	display: none !important;
	}
	@media print {
	.visible-print-block {
	display: block !important;
	}
	}
	.visible-print-inline {
	display: none !important;
	}
	@media print {
	.visible-print-inline {
	display: inline !important;
	}
	}
	.visible-print-inline-block {
	display: none !important;
	}
	@media print {
	.visible-print-inline-block {
	display: inline-block !important;
	}
	}
	@media print {
	.hidden-print {
	display: none !important;
	}
	}
	/*!
	*
	* Font Awesome
	*
	*/
	/*!
	* Font Awesome 4.2.0 by @davegandy - http://fontawesome.io - @fontawesome
	* License - http://fontawesome.io/license (Font: SIL OFL 1.1, CSS: MIT License)
	*/
	/* FONT PATH
	* -------------------------- */
	@font-face {
	font-family: 'FontAwesome';
	src: url('../components/font-awesome/fonts/fontawesome-webfont.eot?v=4.2.0');
	src: url('../components/font-awesome/fonts/fontawesome-webfont.eot?#iefix&v=4.2.0') format('embedded-opentype'), url('../components/font-awesome/fonts/fontawesome-webfont.woff?v=4.2.0') format('woff'), url('../components/font-awesome/fonts/fontawesome-webfont.ttf?v=4.2.0') format('truetype'), url('../components/font-awesome/fonts/fontawesome-webfont.svg?v=4.2.0#fontawesomeregular') format('svg');
	font-weight: normal;
	font-style: normal;
	}
	.fa {
	display: inline-block;
	font: normal normal normal 14px/1 FontAwesome;
	font-size: inherit;
	text-rendering: auto;
	-webkit-font-smoothing: antialiased;
	-moz-osx-font-smoothing: grayscale;
	}
	/* makes the font 33% larger relative to the icon container */
	.fa-lg {
	font-size: 1.33333333em;
	line-height: 0.75em;
	vertical-align: -15%;
	}
	.fa-2x {
	font-size: 2em;
	}
	.fa-3x {
	font-size: 3em;
	}
	.fa-4x {
	font-size: 4em;
	}
	.fa-5x {
	font-size: 5em;
	}
	.fa-fw {
	width: 1.28571429em;
	text-align: center;
	}
	.fa-ul {
	padding-left: 0;
	margin-left: 2.14285714em;
	list-style-type: none;
	}
	.fa-ul > li {
	position: relative;
	}
	.fa-li {
	position: absolute;
	left: -2.14285714em;
	width: 2.14285714em;
	top: 0.14285714em;
	text-align: center;
	}
	.fa-li.fa-lg {
	left: -1.85714286em;
	}
	.fa-border {
	padding: .2em .25em .15em;
	border: solid 0.08em #eee;
	border-radius: .1em;
	}
	.pull-right {
	float: right;
	}
	.pull-left {
	float: left;
	}
	.fa.pull-left {
	margin-right: .3em;
	}
	.fa.pull-right {
	margin-left: .3em;
	}
	.fa-spin {
	-webkit-animation: fa-spin 2s infinite linear;
	animation: fa-spin 2s infinite linear;
	}
	@-webkit-keyframes fa-spin {
	0% {
	-webkit-transform: rotate(0deg);
	transform: rotate(0deg);
	}
	100% {
	-webkit-transform: rotate(359deg);
	transform: rotate(359deg);
	}
	}
	@keyframes fa-spin {
	0% {
	-webkit-transform: rotate(0deg);
	transform: rotate(0deg);
	}
	100% {
	-webkit-transform: rotate(359deg);
	transform: rotate(359deg);
	}
	}
	.fa-rotate-90 {
	filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=1);
	-webkit-transform: rotate(90deg);
	-ms-transform: rotate(90deg);
	transform: rotate(90deg);
	}
	.fa-rotate-180 {
	filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=2);
	-webkit-transform: rotate(180deg);
	-ms-transform: rotate(180deg);
	transform: rotate(180deg);
	}
	.fa-rotate-270 {
	filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=3);
	-webkit-transform: rotate(270deg);
	-ms-transform: rotate(270deg);
	transform: rotate(270deg);
	}
	.fa-flip-horizontal {
	filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=0, mirror=1);
	-webkit-transform: scale(-1, 1);
	-ms-transform: scale(-1, 1);
	transform: scale(-1, 1);
	}
	.fa-flip-vertical {
	filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=2, mirror=1);
	-webkit-transform: scale(1, -1);
	-ms-transform: scale(1, -1);
	transform: scale(1, -1);
	}
	:root .fa-rotate-90,
	:root .fa-rotate-180,
	:root .fa-rotate-270,
	:root .fa-flip-horizontal,
	:root .fa-flip-vertical {
	filter: none;
	}
	.fa-stack {
	position: relative;
	display: inline-block;
	width: 2em;
	height: 2em;
	line-height: 2em;
	vertical-align: middle;
	}
	.fa-stack-1x,
	.fa-stack-2x {
	position: absolute;
	left: 0;
	width: 100%;
	text-align: center;
	}
	.fa-stack-1x {
	line-height: inherit;
	}
	.fa-stack-2x {
	font-size: 2em;
	}
	.fa-inverse {
	color: #fff;
	}
	/* Font Awesome uses the Unicode Private Use Area (PUA) to ensure screen
	readers do not read off random characters that represent icons */
	.fa-glass:before {
	content: "\f000";
	}
	.fa-music:before {
	content: "\f001";
	}
	.fa-search:before {
	content: "\f002";
	}
	.fa-envelope-o:before {
	content: "\f003";
	}
	.fa-heart:before {
	content: "\f004";
	}
	.fa-star:before {
	content: "\f005";
	}
	.fa-star-o:before {
	content: "\f006";
	}
	.fa-user:before {
	content: "\f007";
	}
	.fa-film:before {
	content: "\f008";
	}
	.fa-th-large:before {
	content: "\f009";
	}
	.fa-th:before {
	content: "\f00a";
	}
	.fa-th-list:before {
	content: "\f00b";
	}
	.fa-check:before {
	content: "\f00c";
	}
	.fa-remove:before,
	.fa-close:before,
	.fa-times:before {
	content: "\f00d";
	}
	.fa-search-plus:before {
	content: "\f00e";
	}
	.fa-search-minus:before {
	content: "\f010";
	}
	.fa-power-off:before {
	content: "\f011";
	}
	.fa-signal:before {
	content: "\f012";
	}
	.fa-gear:before,
	.fa-cog:before {
	content: "\f013";
	}
	.fa-trash-o:before {
	content: "\f014";
	}
	.fa-home:before {
	content: "\f015";
	}
	.fa-file-o:before {
	content: "\f016";
	}
	.fa-clock-o:before {
	content: "\f017";
	}
	.fa-road:before {
	content: "\f018";
	}
	.fa-download:before {
	content: "\f019";
	}
	.fa-arrow-circle-o-down:before {
	content: "\f01a";
	}
	.fa-arrow-circle-o-up:before {
	content: "\f01b";
	}
	.fa-inbox:before {
	content: "\f01c";
	}
	.fa-play-circle-o:before {
	content: "\f01d";
	}
	.fa-rotate-right:before,
	.fa-repeat:before {
	content: "\f01e";
	}
	.fa-refresh:before {
	content: "\f021";
	}
	.fa-list-alt:before {
	content: "\f022";
	}
	.fa-lock:before {
	content: "\f023";
	}
	.fa-flag:before {
	content: "\f024";
	}
	.fa-headphones:before {
	content: "\f025";
	}
	.fa-volume-off:before {
	content: "\f026";
	}
	.fa-volume-down:before {
	content: "\f027";
	}
	.fa-volume-up:before {
	content: "\f028";
	}
	.fa-qrcode:before {
	content: "\f029";
	}
	.fa-barcode:before {
	content: "\f02a";
	}
	.fa-tag:before {
	content: "\f02b";
	}
	.fa-tags:before {
	content: "\f02c";
	}
	.fa-book:before {
	content: "\f02d";
	}
	.fa-bookmark:before {
	content: "\f02e";
	}
	.fa-print:before {
	content: "\f02f";
	}
	.fa-camera:before {
	content: "\f030";
	}
	.fa-font:before {
	content: "\f031";
	}
	.fa-bold:before {
	content: "\f032";
	}
	.fa-italic:before {
	content: "\f033";
	}
	.fa-text-height:before {
	content: "\f034";
	}
	.fa-text-width:before {
	content: "\f035";
	}
	.fa-align-left:before {
	content: "\f036";
	}
	.fa-align-center:before {
	content: "\f037";
	}
	.fa-align-right:before {
	content: "\f038";
	}
	.fa-align-justify:before {
	content: "\f039";
	}
	.fa-list:before {
	content: "\f03a";
	}
	.fa-dedent:before,
	.fa-outdent:before {
	content: "\f03b";
	}
	.fa-indent:before {
	content: "\f03c";
	}
	.fa-video-camera:before {
	content: "\f03d";
	}
	.fa-photo:before,
	.fa-image:before,
	.fa-picture-o:before {
	content: "\f03e";
	}
	.fa-pencil:before {
	content: "\f040";
	}
	.fa-map-marker:before {
	content: "\f041";
	}
	.fa-adjust:before {
	content: "\f042";
	}
	.fa-tint:before {
	content: "\f043";
	}
	.fa-edit:before,
	.fa-pencil-square-o:before {
	content: "\f044";
	}
	.fa-share-square-o:before {
	content: "\f045";
	}
	.fa-check-square-o:before {
	content: "\f046";
	}
	.fa-arrows:before {
	content: "\f047";
	}
	.fa-step-backward:before {
	content: "\f048";
	}
	.fa-fast-backward:before {
	content: "\f049";
	}
	.fa-backward:before {
	content: "\f04a";
	}
	.fa-play:before {
	content: "\f04b";
	}
	.fa-pause:before {
	content: "\f04c";
	}
	.fa-stop:before {
	content: "\f04d";
	}
	.fa-forward:before {
	content: "\f04e";
	}
	.fa-fast-forward:before {
	content: "\f050";
	}
	.fa-step-forward:before {
	content: "\f051";
	}
	.fa-eject:before {
	content: "\f052";
	}
	.fa-chevron-left:before {
	content: "\f053";
	}
	.fa-chevron-right:before {
	content: "\f054";
	}
	.fa-plus-circle:before {
	content: "\f055";
	}
	.fa-minus-circle:before {
	content: "\f056";
	}
	.fa-times-circle:before {
	content: "\f057";
	}
	.fa-check-circle:before {
	content: "\f058";
	}
	.fa-question-circle:before {
	content: "\f059";
	}
	.fa-info-circle:before {
	content: "\f05a";
	}
	.fa-crosshairs:before {
	content: "\f05b";
	}
	.fa-times-circle-o:before {
	content: "\f05c";
	}
	.fa-check-circle-o:before {
	content: "\f05d";
	}
	.fa-ban:before {
	content: "\f05e";
	}
	.fa-arrow-left:before {
	content: "\f060";
	}
	.fa-arrow-right:before {
	content: "\f061";
	}
	.fa-arrow-up:before {
	content: "\f062";
	}
	.fa-arrow-down:before {
	content: "\f063";
	}
	.fa-mail-forward:before,
	.fa-share:before {
	content: "\f064";
	}
	.fa-expand:before {
	content: "\f065";
	}
	.fa-compress:before {
	content: "\f066";
	}
	.fa-plus:before {
	content: "\f067";
	}
	.fa-minus:before {
	content: "\f068";
	}
	.fa-asterisk:before {
	content: "\f069";
	}
	.fa-exclamation-circle:before {
	content: "\f06a";
	}
	.fa-gift:before {
	content: "\f06b";
	}
	.fa-leaf:before {
	content: "\f06c";
	}
	.fa-fire:before {
	content: "\f06d";
	}
	.fa-eye:before {
	content: "\f06e";
	}
	.fa-eye-slash:before {
	content: "\f070";
	}
	.fa-warning:before,
	.fa-exclamation-triangle:before {
	content: "\f071";
	}
	.fa-plane:before {
	content: "\f072";
	}
	.fa-calendar:before {
	content: "\f073";
	}
	.fa-random:before {
	content: "\f074";
	}
	.fa-comment:before {
	content: "\f075";
	}
	.fa-magnet:before {
	content: "\f076";
	}
	.fa-chevron-up:before {
	content: "\f077";
	}
	.fa-chevron-down:before {
	content: "\f078";
	}
	.fa-retweet:before {
	content: "\f079";
	}
	.fa-shopping-cart:before {
	content: "\f07a";
	}
	.fa-folder:before {
	content: "\f07b";
	}
	.fa-folder-open:before {
	content: "\f07c";
	}
	.fa-arrows-v:before {
	content: "\f07d";
	}
	.fa-arrows-h:before {
	content: "\f07e";
	}
	.fa-bar-chart-o:before,
	.fa-bar-chart:before {
	content: "\f080";
	}
	.fa-twitter-square:before {
	content: "\f081";
	}
	.fa-facebook-square:before {
	content: "\f082";
	}
	.fa-camera-retro:before {
	content: "\f083";
	}
	.fa-key:before {
	content: "\f084";
	}
	.fa-gears:before,
	.fa-cogs:before {
	content: "\f085";
	}
	.fa-comments:before {
	content: "\f086";
	}
	.fa-thumbs-o-up:before {
	content: "\f087";
	}
	.fa-thumbs-o-down:before {
	content: "\f088";
	}
	.fa-star-half:before {
	content: "\f089";
	}
	.fa-heart-o:before {
	content: "\f08a";
	}
	.fa-sign-out:before {
	content: "\f08b";
	}
	.fa-linkedin-square:before {
	content: "\f08c";
	}
	.fa-thumb-tack:before {
	content: "\f08d";
	}
	.fa-external-link:before {
	content: "\f08e";
	}
	.fa-sign-in:before {
	content: "\f090";
	}
	.fa-trophy:before {
	content: "\f091";
	}
	.fa-github-square:before {
	content: "\f092";
	}
	.fa-upload:before {
	content: "\f093";
	}
	.fa-lemon-o:before {
	content: "\f094";
	}
	.fa-phone:before {
	content: "\f095";
	}
	.fa-square-o:before {
	content: "\f096";
	}
	.fa-bookmark-o:before {
	content: "\f097";
	}
	.fa-phone-square:before {
	content: "\f098";
	}
	.fa-twitter:before {
	content: "\f099";
	}
	.fa-facebook:before {
	content: "\f09a";
	}
	.fa-github:before {
	content: "\f09b";
	}
	.fa-unlock:before {
	content: "\f09c";
	}
	.fa-credit-card:before {
	content: "\f09d";
	}
	.fa-rss:before {
	content: "\f09e";
	}
	.fa-hdd-o:before {
	content: "\f0a0";
	}
	.fa-bullhorn:before {
	content: "\f0a1";
	}
	.fa-bell:before {
	content: "\f0f3";
	}
	.fa-certificate:before {
	content: "\f0a3";
	}
	.fa-hand-o-right:before {
	content: "\f0a4";
	}
	.fa-hand-o-left:before {
	content: "\f0a5";
	}
	.fa-hand-o-up:before {
	content: "\f0a6";
	}
	.fa-hand-o-down:before {
	content: "\f0a7";
	}
	.fa-arrow-circle-left:before {
	content: "\f0a8";
	}
	.fa-arrow-circle-right:before {
	content: "\f0a9";
	}
	.fa-arrow-circle-up:before {
	content: "\f0aa";
	}
	.fa-arrow-circle-down:before {
	content: "\f0ab";
	}
	.fa-globe:before {
	content: "\f0ac";
	}
	.fa-wrench:before {
	content: "\f0ad";
	}
	.fa-tasks:before {
	content: "\f0ae";
	}
	.fa-filter:before {
	content: "\f0b0";
	}
	.fa-briefcase:before {
	content: "\f0b1";
	}
	.fa-arrows-alt:before {
	content: "\f0b2";
	}
	.fa-group:before,
	.fa-users:before {
	content: "\f0c0";
	}
	.fa-chain:before,
	.fa-link:before {
	content: "\f0c1";
	}
	.fa-cloud:before {
	content: "\f0c2";
	}
	.fa-flask:before {
	content: "\f0c3";
	}
	.fa-cut:before,
	.fa-scissors:before {
	content: "\f0c4";
	}
	.fa-copy:before,
	.fa-files-o:before {
	content: "\f0c5";
	}
	.fa-paperclip:before {
	content: "\f0c6";
	}
	.fa-save:before,
	.fa-floppy-o:before {
	content: "\f0c7";
	}
	.fa-square:before {
	content: "\f0c8";
	}
	.fa-navicon:before,
	.fa-reorder:before,
	.fa-bars:before {
	content: "\f0c9";
	}
	.fa-list-ul:before {
	content: "\f0ca";
	}
	.fa-list-ol:before {
	content: "\f0cb";
	}
	.fa-strikethrough:before {
	content: "\f0cc";
	}
	.fa-underline:before {
	content: "\f0cd";
	}
	.fa-table:before {
	content: "\f0ce";
	}
	.fa-magic:before {
	content: "\f0d0";
	}
	.fa-truck:before {
	content: "\f0d1";
	}
	.fa-pinterest:before {
	content: "\f0d2";
	}
	.fa-pinterest-square:before {
	content: "\f0d3";
	}
	.fa-google-plus-square:before {
	content: "\f0d4";
	}
	.fa-google-plus:before {
	content: "\f0d5";
	}
	.fa-money:before {
	content: "\f0d6";
	}
	.fa-caret-down:before {
	content: "\f0d7";
	}
	.fa-caret-up:before {
	content: "\f0d8";
	}
	.fa-caret-left:before {
	content: "\f0d9";
	}
	.fa-caret-right:before {
	content: "\f0da";
	}
	.fa-columns:before {
	content: "\f0db";
	}
	.fa-unsorted:before,
	.fa-sort:before {
	content: "\f0dc";
	}
	.fa-sort-down:before,
	.fa-sort-desc:before {
	content: "\f0dd";
	}
	.fa-sort-up:before,
	.fa-sort-asc:before {
	content: "\f0de";
	}
	.fa-envelope:before {
	content: "\f0e0";
	}
	.fa-linkedin:before {
	content: "\f0e1";
	}
	.fa-rotate-left:before,
	.fa-undo:before {
	content: "\f0e2";
	}
	.fa-legal:before,
	.fa-gavel:before {
	content: "\f0e3";
	}
	.fa-dashboard:before,
	.fa-tachometer:before {
	content: "\f0e4";
	}
	.fa-comment-o:before {
	content: "\f0e5";
	}
	.fa-comments-o:before {
	content: "\f0e6";
	}
	.fa-flash:before,
	.fa-bolt:before {
	content: "\f0e7";
	}
	.fa-sitemap:before {
	content: "\f0e8";
	}
	.fa-umbrella:before {
	content: "\f0e9";
	}
	.fa-paste:before,
	.fa-clipboard:before {
	content: "\f0ea";
	}
	.fa-lightbulb-o:before {
	content: "\f0eb";
	}
	.fa-exchange:before {
	content: "\f0ec";
	}
	.fa-cloud-download:before {
	content: "\f0ed";
	}
	.fa-cloud-upload:before {
	content: "\f0ee";
	}
	.fa-user-md:before {
	content: "\f0f0";
	}
	.fa-stethoscope:before {
	content: "\f0f1";
	}
	.fa-suitcase:before {
	content: "\f0f2";
	}
	.fa-bell-o:before {
	content: "\f0a2";
	}
	.fa-coffee:before {
	content: "\f0f4";
	}
	.fa-cutlery:before {
	content: "\f0f5";
	}
	.fa-file-text-o:before {
	content: "\f0f6";
	}
	.fa-building-o:before {
	content: "\f0f7";
	}
	.fa-hospital-o:before {
	content: "\f0f8";
	}
	.fa-ambulance:before {
	content: "\f0f9";
	}
	.fa-medkit:before {
	content: "\f0fa";
	}
	.fa-fighter-jet:before {
	content: "\f0fb";
	}
	.fa-beer:before {
	content: "\f0fc";
	}
	.fa-h-square:before {
	content: "\f0fd";
	}
	.fa-plus-square:before {
	content: "\f0fe";
	}
	.fa-angle-double-left:before {
	content: "\f100";
	}
	.fa-angle-double-right:before {
	content: "\f101";
	}
	.fa-angle-double-up:before {
	content: "\f102";
	}
	.fa-angle-double-down:before {
	content: "\f103";
	}
	.fa-angle-left:before {
	content: "\f104";
	}
	.fa-angle-right:before {
	content: "\f105";
	}
	.fa-angle-up:before {
	content: "\f106";
	}
	.fa-angle-down:before {
	content: "\f107";
	}
	.fa-desktop:before {
	content: "\f108";
	}
	.fa-laptop:before {
	content: "\f109";
	}
	.fa-tablet:before {
	content: "\f10a";
	}
	.fa-mobile-phone:before,
	.fa-mobile:before {
	content: "\f10b";
	}
	.fa-circle-o:before {
	content: "\f10c";
	}
	.fa-quote-left:before {
	content: "\f10d";
	}
	.fa-quote-right:before {
	content: "\f10e";
	}
	.fa-spinner:before {
	content: "\f110";
	}
	.fa-circle:before {
	content: "\f111";
	}
	.fa-mail-reply:before,
	.fa-reply:before {
	content: "\f112";
	}
	.fa-github-alt:before {
	content: "\f113";
	}
	.fa-folder-o:before {
	content: "\f114";
	}
	.fa-folder-open-o:before {
	content: "\f115";
	}
	.fa-smile-o:before {
	content: "\f118";
	}
	.fa-frown-o:before {
	content: "\f119";
	}
	.fa-meh-o:before {
	content: "\f11a";
	}
	.fa-gamepad:before {
	content: "\f11b";
	}
	.fa-keyboard-o:before {
	content: "\f11c";
	}
	.fa-flag-o:before {
	content: "\f11d";
	}
	.fa-flag-checkered:before {
	content: "\f11e";
	}
	.fa-terminal:before {
	content: "\f120";
	}
	.fa-code:before {
	content: "\f121";
	}
	.fa-mail-reply-all:before,
	.fa-reply-all:before {
	content: "\f122";
	}
	.fa-star-half-empty:before,
	.fa-star-half-full:before,
	.fa-star-half-o:before {
	content: "\f123";
	}
	.fa-location-arrow:before {
	content: "\f124";
	}
	.fa-crop:before {
	content: "\f125";
	}
	.fa-code-fork:before {
	content: "\f126";
	}
	.fa-unlink:before,
	.fa-chain-broken:before {
	content: "\f127";
	}
	.fa-question:before {
	content: "\f128";
	}
	.fa-info:before {
	content: "\f129";
	}
	.fa-exclamation:before {
	content: "\f12a";
	}
	.fa-superscript:before {
	content: "\f12b";
	}
	.fa-subscript:before {
	content: "\f12c";
	}
	.fa-eraser:before {
	content: "\f12d";
	}
	.fa-puzzle-piece:before {
	content: "\f12e";
	}
	.fa-microphone:before {
	content: "\f130";
	}
	.fa-microphone-slash:before {
	content: "\f131";
	}
	.fa-shield:before {
	content: "\f132";
	}
	.fa-calendar-o:before {
	content: "\f133";
	}
	.fa-fire-extinguisher:before {
	content: "\f134";
	}
	.fa-rocket:before {
	content: "\f135";
	}
	.fa-maxcdn:before {
	content: "\f136";
	}
	.fa-chevron-circle-left:before {
	content: "\f137";
	}
	.fa-chevron-circle-right:before {
	content: "\f138";
	}
	.fa-chevron-circle-up:before {
	content: "\f139";
	}
	.fa-chevron-circle-down:before {
	content: "\f13a";
	}
	.fa-html5:before {
	content: "\f13b";
	}
	.fa-css3:before {
	content: "\f13c";
	}
	.fa-anchor:before {
	content: "\f13d";
	}
	.fa-unlock-alt:before {
	content: "\f13e";
	}
	.fa-bullseye:before {
	content: "\f140";
	}
	.fa-ellipsis-h:before {
	content: "\f141";
	}
	.fa-ellipsis-v:before {
	content: "\f142";
	}
	.fa-rss-square:before {
	content: "\f143";
	}
	.fa-play-circle:before {
	content: "\f144";
	}
	.fa-ticket:before {
	content: "\f145";
	}
	.fa-minus-square:before {
	content: "\f146";
	}
	.fa-minus-square-o:before {
	content: "\f147";
	}
	.fa-level-up:before {
	content: "\f148";
	}
	.fa-level-down:before {
	content: "\f149";
	}
	.fa-check-square:before {
	content: "\f14a";
	}
	.fa-pencil-square:before {
	content: "\f14b";
	}
	.fa-external-link-square:before {
	content: "\f14c";
	}
	.fa-share-square:before {
	content: "\f14d";
	}
	.fa-compass:before {
	content: "\f14e";
	}
	.fa-toggle-down:before,
	.fa-caret-square-o-down:before {
	content: "\f150";
	}
	.fa-toggle-up:before,
	.fa-caret-square-o-up:before {
	content: "\f151";
	}
	.fa-toggle-right:before,
	.fa-caret-square-o-right:before {
	content: "\f152";
	}
	.fa-euro:before,
	.fa-eur:before {
	content: "\f153";
	}
	.fa-gbp:before {
	content: "\f154";
	}
	.fa-dollar:before,
	.fa-usd:before {
	content: "\f155";
	}
	.fa-rupee:before,
	.fa-inr:before {
	content: "\f156";
	}
	.fa-cny:before,
	.fa-rmb:before,
	.fa-yen:before,
	.fa-jpy:before {
	content: "\f157";
	}
	.fa-ruble:before,
	.fa-rouble:before,
	.fa-rub:before {
	content: "\f158";
	}
	.fa-won:before,
	.fa-krw:before {
	content: "\f159";
	}
	.fa-bitcoin:before,
	.fa-btc:before {
	content: "\f15a";
	}
	.fa-file:before {
	content: "\f15b";
	}
	.fa-file-text:before {
	content: "\f15c";
	}
	.fa-sort-alpha-asc:before {
	content: "\f15d";
	}
	.fa-sort-alpha-desc:before {
	content: "\f15e";
	}
	.fa-sort-amount-asc:before {
	content: "\f160";
	}
	.fa-sort-amount-desc:before {
	content: "\f161";
	}
	.fa-sort-numeric-asc:before {
	content: "\f162";
	}
	.fa-sort-numeric-desc:before {
	content: "\f163";
	}
	.fa-thumbs-up:before {
	content: "\f164";
	}
	.fa-thumbs-down:before {
	content: "\f165";
	}
	.fa-youtube-square:before {
	content: "\f166";
	}
	.fa-youtube:before {
	content: "\f167";
	}
	.fa-xing:before {
	content: "\f168";
	}
	.fa-xing-square:before {
	content: "\f169";
	}
	.fa-youtube-play:before {
	content: "\f16a";
	}
	.fa-dropbox:before {
	content: "\f16b";
	}
	.fa-stack-overflow:before {
	content: "\f16c";
	}
	.fa-instagram:before {
	content: "\f16d";
	}
	.fa-flickr:before {
	content: "\f16e";
	}
	.fa-adn:before {
	content: "\f170";
	}
	.fa-bitbucket:before {
	content: "\f171";
	}
	.fa-bitbucket-square:before {
	content: "\f172";
	}
	.fa-tumblr:before {
	content: "\f173";
	}
	.fa-tumblr-square:before {
	content: "\f174";
	}
	.fa-long-arrow-down:before {
	content: "\f175";
	}
	.fa-long-arrow-up:before {
	content: "\f176";
	}
	.fa-long-arrow-left:before {
	content: "\f177";
	}
	.fa-long-arrow-right:before {
	content: "\f178";
	}
	.fa-apple:before {
	content: "\f179";
	}
	.fa-windows:before {
	content: "\f17a";
	}
	.fa-android:before {
	content: "\f17b";
	}
	.fa-linux:before {
	content: "\f17c";
	}
	.fa-dribbble:before {
	content: "\f17d";
	}
	.fa-skype:before {
	content: "\f17e";
	}
	.fa-foursquare:before {
	content: "\f180";
	}
	.fa-trello:before {
	content: "\f181";
	}
	.fa-female:before {
	content: "\f182";
	}
	.fa-male:before {
	content: "\f183";
	}
	.fa-gittip:before {
	content: "\f184";
	}
	.fa-sun-o:before {
	content: "\f185";
	}
	.fa-moon-o:before {
	content: "\f186";
	}
	.fa-archive:before {
	content: "\f187";
	}
	.fa-bug:before {
	content: "\f188";
	}
	.fa-vk:before {
	content: "\f189";
	}
	.fa-weibo:before {
	content: "\f18a";
	}
	.fa-renren:before {
	content: "\f18b";
	}
	.fa-pagelines:before {
	content: "\f18c";
	}
	.fa-stack-exchange:before {
	content: "\f18d";
	}
	.fa-arrow-circle-o-right:before {
	content: "\f18e";
	}
	.fa-arrow-circle-o-left:before {
	content: "\f190";
	}
	.fa-toggle-left:before,
	.fa-caret-square-o-left:before {
	content: "\f191";
	}
	.fa-dot-circle-o:before {
	content: "\f192";
	}
	.fa-wheelchair:before {
	content: "\f193";
	}
	.fa-vimeo-square:before {
	content: "\f194";
	}
	.fa-turkish-lira:before,
	.fa-try:before {
	content: "\f195";
	}
	.fa-plus-square-o:before {
	content: "\f196";
	}
	.fa-space-shuttle:before {
	content: "\f197";
	}
	.fa-slack:before {
	content: "\f198";
	}
	.fa-envelope-square:before {
	content: "\f199";
	}
	.fa-wordpress:before {
	content: "\f19a";
	}
	.fa-openid:before {
	content: "\f19b";
	}
	.fa-institution:before,
	.fa-bank:before,
	.fa-university:before {
	content: "\f19c";
	}
	.fa-mortar-board:before,
	.fa-graduation-cap:before {
	content: "\f19d";
	}
	.fa-yahoo:before {
	content: "\f19e";
	}
	.fa-google:before {
	content: "\f1a0";
	}
	.fa-reddit:before {
	content: "\f1a1";
	}
	.fa-reddit-square:before {
	content: "\f1a2";
	}
	.fa-stumbleupon-circle:before {
	content: "\f1a3";
	}
	.fa-stumbleupon:before {
	content: "\f1a4";
	}
	.fa-delicious:before {
	content: "\f1a5";
	}
	.fa-digg:before {
	content: "\f1a6";
	}
	.fa-pied-piper:before {
	content: "\f1a7";
	}
	.fa-pied-piper-alt:before {
	content: "\f1a8";
	}
	.fa-drupal:before {
	content: "\f1a9";
	}
	.fa-joomla:before {
	content: "\f1aa";
	}
	.fa-language:before {
	content: "\f1ab";
	}
	.fa-fax:before {
	content: "\f1ac";
	}
	.fa-building:before {
	content: "\f1ad";
	}
	.fa-child:before {
	content: "\f1ae";
	}
	.fa-paw:before {
	content: "\f1b0";
	}
	.fa-spoon:before {
	content: "\f1b1";
	}
	.fa-cube:before {
	content: "\f1b2";
	}
	.fa-cubes:before {
	content: "\f1b3";
	}
	.fa-behance:before {
	content: "\f1b4";
	}
	.fa-behance-square:before {
	content: "\f1b5";
	}
	.fa-steam:before {
	content: "\f1b6";
	}
	.fa-steam-square:before {
	content: "\f1b7";
	}
	.fa-recycle:before {
	content: "\f1b8";
	}
	.fa-automobile:before,
	.fa-car:before {
	content: "\f1b9";
	}
	.fa-cab:before,
	.fa-taxi:before {
	content: "\f1ba";
	}
	.fa-tree:before {
	content: "\f1bb";
	}
	.fa-spotify:before {
	content: "\f1bc";
	}
	.fa-deviantart:before {
	content: "\f1bd";
	}
	.fa-soundcloud:before {
	content: "\f1be";
	}
	.fa-database:before {
	content: "\f1c0";
	}
	.fa-file-pdf-o:before {
	content: "\f1c1";
	}
	.fa-file-word-o:before {
	content: "\f1c2";
	}
	.fa-file-excel-o:before {
	content: "\f1c3";
	}
	.fa-file-powerpoint-o:before {
	content: "\f1c4";
	}
	.fa-file-photo-o:before,
	.fa-file-picture-o:before,
	.fa-file-image-o:before {
	content: "\f1c5";
	}
	.fa-file-zip-o:before,
	.fa-file-archive-o:before {
	content: "\f1c6";
	}
	.fa-file-sound-o:before,
	.fa-file-audio-o:before {
	content: "\f1c7";
	}
	.fa-file-movie-o:before,
	.fa-file-video-o:before {
	content: "\f1c8";
	}
	.fa-file-code-o:before {
	content: "\f1c9";
	}
	.fa-vine:before {
	content: "\f1ca";
	}
	.fa-codepen:before {
	content: "\f1cb";
	}
	.fa-jsfiddle:before {
	content: "\f1cc";
	}
	.fa-life-bouy:before,
	.fa-life-buoy:before,
	.fa-life-saver:before,
	.fa-support:before,
	.fa-life-ring:before {
	content: "\f1cd";
	}
	.fa-circle-o-notch:before {
	content: "\f1ce";
	}
	.fa-ra:before,
	.fa-rebel:before {
	content: "\f1d0";
	}
	.fa-ge:before,
	.fa-empire:before {
	content: "\f1d1";
	}
	.fa-git-square:before {
	content: "\f1d2";
	}
	.fa-git:before {
	content: "\f1d3";
	}
	.fa-hacker-news:before {
	content: "\f1d4";
	}
	.fa-tencent-weibo:before {
	content: "\f1d5";
	}
	.fa-qq:before {
	content: "\f1d6";
	}
	.fa-wechat:before,
	.fa-weixin:before {
	content: "\f1d7";
	}
	.fa-send:before,
	.fa-paper-plane:before {
	content: "\f1d8";
	}
	.fa-send-o:before,
	.fa-paper-plane-o:before {
	content: "\f1d9";
	}
	.fa-history:before {
	content: "\f1da";
	}
	.fa-circle-thin:before {
	content: "\f1db";
	}
	.fa-header:before {
	content: "\f1dc";
	}
	.fa-paragraph:before {
	content: "\f1dd";
	}
	.fa-sliders:before {
	content: "\f1de";
	}
	.fa-share-alt:before {
	content: "\f1e0";
	}
	.fa-share-alt-square:before {
	content: "\f1e1";
	}
	.fa-bomb:before {
	content: "\f1e2";
	}
	.fa-soccer-ball-o:before,
	.fa-futbol-o:before {
	content: "\f1e3";
	}
	.fa-tty:before {
	content: "\f1e4";
	}
	.fa-binoculars:before {
	content: "\f1e5";
	}
	.fa-plug:before {
	content: "\f1e6";
	}
	.fa-slideshare:before {
	content: "\f1e7";
	}
	.fa-twitch:before {
	content: "\f1e8";
	}
	.fa-yelp:before {
	content: "\f1e9";
	}
	.fa-newspaper-o:before {
	content: "\f1ea";
	}
	.fa-wifi:before {
	content: "\f1eb";
	}
	.fa-calculator:before {
	content: "\f1ec";
	}
	.fa-paypal:before {
	content: "\f1ed";
	}
	.fa-google-wallet:before {
	content: "\f1ee";
	}
	.fa-cc-visa:before {
	content: "\f1f0";
	}
	.fa-cc-mastercard:before {
	content: "\f1f1";
	}
	.fa-cc-discover:before {
	content: "\f1f2";
	}
	.fa-cc-amex:before {
	content: "\f1f3";
	}
	.fa-cc-paypal:before {
	content: "\f1f4";
	}
	.fa-cc-stripe:before {
	content: "\f1f5";
	}
	.fa-bell-slash:before {
	content: "\f1f6";
	}
	.fa-bell-slash-o:before {
	content: "\f1f7";
	}
	.fa-trash:before {
	content: "\f1f8";
	}
	.fa-copyright:before {
	content: "\f1f9";
	}
	.fa-at:before {
	content: "\f1fa";
	}
	.fa-eyedropper:before {
	content: "\f1fb";
	}
	.fa-paint-brush:before {
	content: "\f1fc";
	}
	.fa-birthday-cake:before {
	content: "\f1fd";
	}
	.fa-area-chart:before {
	content: "\f1fe";
	}
	.fa-pie-chart:before {
	content: "\f200";
	}
	.fa-line-chart:before {
	content: "\f201";
	}
	.fa-lastfm:before {
	content: "\f202";
	}
	.fa-lastfm-square:before {
	content: "\f203";
	}
	.fa-toggle-off:before {
	content: "\f204";
	}
	.fa-toggle-on:before {
	content: "\f205";
	}
	.fa-bicycle:before {
	content: "\f206";
	}
	.fa-bus:before {
	content: "\f207";
	}
	.fa-ioxhost:before {
	content: "\f208";
	}
	.fa-angellist:before {
	content: "\f209";
	}
	.fa-cc:before {
	content: "\f20a";
	}
	.fa-shekel:before,
	.fa-sheqel:before,
	.fa-ils:before {
	content: "\f20b";
	}
	.fa-meanpath:before {
	content: "\f20c";
	}
	/*!
	*
	* IPython base
	*
	*/
	.modal.fade .modal-dialog {
	-webkit-transform: translate(0, 0);
	-ms-transform: translate(0, 0);
	-o-transform: translate(0, 0);
	transform: translate(0, 0);
	}
	code {
	color: #000;
	}
	pre {
	font-size: inherit;
	line-height: inherit;
	}
	label {
	font-weight: normal;
	}
	/* Make the page background atleast 100% the height of the view port */
	/* Make the page itself atleast 70% the height of the view port */
	.border-box-sizing {
	box-sizing: border-box;
	-moz-box-sizing: border-box;
	-webkit-box-sizing: border-box;
	}
	.corner-all {
	border-radius: 2px;
	}
	.no-padding {
	padding: 0px;
	}
	/* Flexible box model classes */
	/* Taken from Alex Russell http://infrequently.org/2009/08/css-3-progress/ */
	/* This file is a compatability layer. It allows the usage of flexible box
	model layouts accross multiple browsers, including older browsers. The newest,
	universal implementation of the flexible box model is used when available (see
	`Modern browsers` comments below). Browsers that are known to implement this
	new spec completely include:

	Firefox 28.0+
	Chrome 29.0+
	Internet Explorer 11+
	Opera 17.0+

	Browsers not listed, including Safari, are supported via the styling under the
	`Old browsers` comments below.
	*/
	.hbox {
	/* Old browsers */
	display: -webkit-box;
	-webkit-box-orient: horizontal;
	-webkit-box-align: stretch;
	display: -moz-box;
	-moz-box-orient: horizontal;
	-moz-box-align: stretch;
	display: box;
	box-orient: horizontal;
	box-align: stretch;
	/* Modern browsers */
	display: flex;
	flex-direction: row;
	align-items: stretch;
	}
	.hbox > * {
	/* Old browsers */
	-webkit-box-flex: 0;
	-moz-box-flex: 0;
	box-flex: 0;
	/* Modern browsers */
	flex: none;
	}
	.vbox {
	/* Old browsers */
	display: -webkit-box;
	-webkit-box-orient: vertical;
	-webkit-box-align: stretch;
	display: -moz-box;
	-moz-box-orient: vertical;
	-moz-box-align: stretch;
	display: box;
	box-orient: vertical;
	box-align: stretch;
	/* Modern browsers */
	display: flex;
	flex-direction: column;
	align-items: stretch;
	}
	.vbox > * {
	/* Old browsers */
	-webkit-box-flex: 0;
	-moz-box-flex: 0;
	box-flex: 0;
	/* Modern browsers */
	flex: none;
	}
	.hbox.reverse,
	.vbox.reverse,
	.reverse {
	/* Old browsers */
	-webkit-box-direction: reverse;
	-moz-box-direction: reverse;
	box-direction: reverse;
	/* Modern browsers */
	flex-direction: row-reverse;
	}
	.hbox.box-flex0,
	.vbox.box-flex0,
	.box-flex0 {
	/* Old browsers */
	-webkit-box-flex: 0;
	-moz-box-flex: 0;
	box-flex: 0;
	/* Modern browsers */
	flex: none;
	width: auto;
	}
	.hbox.box-flex1,
	.vbox.box-flex1,
	.box-flex1 {
	/* Old browsers */
	-webkit-box-flex: 1;
	-moz-box-flex: 1;
	box-flex: 1;
	/* Modern browsers */
	flex: 1;
	}
	.hbox.box-flex,
	.vbox.box-flex,
	.box-flex {
	/* Old browsers */
	/* Old browsers */
	-webkit-box-flex: 1;
	-moz-box-flex: 1;
	box-flex: 1;
	/* Modern browsers */
	flex: 1;
	}
	.hbox.box-flex2,
	.vbox.box-flex2,
	.box-flex2 {
	/* Old browsers */
	-webkit-box-flex: 2;
	-moz-box-flex: 2;
	box-flex: 2;
	/* Modern browsers */
	flex: 2;
	}
	.box-group1 {
	/* Deprecated */
	-webkit-box-flex-group: 1;
	-moz-box-flex-group: 1;
	box-flex-group: 1;
	}
	.box-group2 {
	/* Deprecated */
	-webkit-box-flex-group: 2;
	-moz-box-flex-group: 2;
	box-flex-group: 2;
	}
	.hbox.start,
	.vbox.start,
	.start {
	/* Old browsers */
	-webkit-box-pack: start;
	-moz-box-pack: start;
	box-pack: start;
	/* Modern browsers */
	justify-content: flex-start;
	}
	.hbox.end,
	.vbox.end,
	.end {
	/* Old browsers */
	-webkit-box-pack: end;
	-moz-box-pack: end;
	box-pack: end;
	/* Modern browsers */
	justify-content: flex-end;
	}
	.hbox.center,
	.vbox.center,
	.center {
	/* Old browsers */
	-webkit-box-pack: center;
	-moz-box-pack: center;
	box-pack: center;
	/* Modern browsers */
	justify-content: center;
	}
	.hbox.baseline,
	.vbox.baseline,
	.baseline {
	/* Old browsers */
	-webkit-box-pack: baseline;
	-moz-box-pack: baseline;
	box-pack: baseline;
	/* Modern browsers */
	justify-content: baseline;
	}
	.hbox.stretch,
	.vbox.stretch,
	.stretch {
	/* Old browsers */
	-webkit-box-pack: stretch;
	-moz-box-pack: stretch;
	box-pack: stretch;
	/* Modern browsers */
	justify-content: stretch;
	}
	.hbox.align-start,
	.vbox.align-start,
	.align-start {
	/* Old browsers */
	-webkit-box-align: start;
	-moz-box-align: start;
	box-align: start;
	/* Modern browsers */
	align-items: flex-start;
	}
	.hbox.align-end,
	.vbox.align-end,
	.align-end {
	/* Old browsers */
	-webkit-box-align: end;
	-moz-box-align: end;
	box-align: end;
	/* Modern browsers */
	align-items: flex-end;
	}
	.hbox.align-center,
	.vbox.align-center,
	.align-center {
	/* Old browsers */
	-webkit-box-align: center;
	-moz-box-align: center;
	box-align: center;
	/* Modern browsers */
	align-items: center;
	}
	.hbox.align-baseline,
	.vbox.align-baseline,
	.align-baseline {
	/* Old browsers */
	-webkit-box-align: baseline;
	-moz-box-align: baseline;
	box-align: baseline;
	/* Modern browsers */
	align-items: baseline;
	}
	.hbox.align-stretch,
	.vbox.align-stretch,
	.align-stretch {
	/* Old browsers */
	-webkit-box-align: stretch;
	-moz-box-align: stretch;
	box-align: stretch;
	/* Modern browsers */
	align-items: stretch;
	}
	div.error {
	margin: 2em;
	text-align: center;
	}
	div.error > h1 {
	font-size: 500%;
	line-height: normal;
	}
	div.error > p {
	font-size: 200%;
	line-height: normal;
	}
	div.traceback-wrapper {
	text-align: left;
	max-width: 800px;
	margin: auto;
	}
	/**
	* Primary styles
	*
	* Author: Jupyter Development Team
	*/
	body {
	background-color: #fff;
	/* This makes sure that the body covers the entire window and needs to
	be in a different element than the display: box in wrapper below */
	position: absolute;
	left: 0px;
	right: 0px;
	top: 0px;
	bottom: 0px;
	overflow: visible;
	}
	body > #header {
	/* Initially hidden to prevent FLOUC */
	display: none;
	background-color: #fff;
	/* Display over codemirror */
	position: relative;
	z-index: 100;
	}
	body > #header #header-container {
	padding-bottom: 5px;
	padding-top: 5px;
	box-sizing: border-box;
	-moz-box-sizing: border-box;
	-webkit-box-sizing: border-box;
	}
	body > #header .header-bar {
	width: 100%;
	height: 1px;
	background: #e7e7e7;
	margin-bottom: -1px;
	}
	@media print {
	body > #header {
	display: none !important;
	}
	}
	#header-spacer {
	width: 100%;
	visibility: hidden;
	}
	@media print {
	#header-spacer {
	display: none;
	}
	}
	#ipython_notebook {
	padding-left: 0px;
	padding-top: 1px;
	padding-bottom: 1px;
	}
	@media (max-width: 991px) {
	#ipython_notebook {
	margin-left: 10px;
	}
	}
	[dir="rtl"] #ipython_notebook {
	float: right !important;
	}
	#noscript {
	width: auto;
	padding-top: 16px;
	padding-bottom: 16px;
	text-align: center;
	font-size: 22px;
	color: red;
	font-weight: bold;
	}
	#ipython_notebook img {
	height: 28px;
	}
	#site {
	width: 100%;
	display: none;
	box-sizing: border-box;
	-moz-box-sizing: border-box;
	-webkit-box-sizing: border-box;
	overflow: auto;
	}
	@media print {
	#site {
	height: auto !important;
	}
	}
	/* Smaller buttons */
	.ui-button .ui-button-text {
	padding: 0.2em 0.8em;
	font-size: 77%;
	}
	input.ui-button {
	padding: 0.3em 0.9em;
	}
	span#login_widget {
	float: right;
	}
	span#login_widget > .button,
	#logout {
	color: #333;
	background-color: #fff;
	border-color: #ccc;
	}
	span#login_widget > .button:focus,
	#logout:focus,
	span#login_widget > .button.focus,
	#logout.focus {
	color: #333;
	background-color: #e6e6e6;
	border-color: #8c8c8c;
	}
	span#login_widget > .button:hover,
	#logout:hover {
	color: #333;
	background-color: #e6e6e6;
	border-color: #adadad;
	}
	span#login_widget > .button:active,
	#logout:active,
	span#login_widget > .button.active,
	#logout.active,
	.open > .dropdown-togglespan#login_widget > .button,
	.open > .dropdown-toggle#logout {
	color: #333;
	background-color: #e6e6e6;
	border-color: #adadad;
	}
	span#login_widget > .button:active:hover,
	#logout:active:hover,
	span#login_widget > .button.active:hover,
	#logout.active:hover,
	.open > .dropdown-togglespan#login_widget > .button:hover,
	.open > .dropdown-toggle#logout:hover,
	span#login_widget > .button:active:focus,
	#logout:active:focus,
	span#login_widget > .button.active:focus,
	#logout.active:focus,
	.open > .dropdown-togglespan#login_widget > .button:focus,
	.open > .dropdown-toggle#logout:focus,
	span#login_widget > .button:active.focus,
	#logout:active.focus,
	span#login_widget > .button.active.focus,
	#logout.active.focus,
	.open > .dropdown-togglespan#login_widget > .button.focus,
	.open > .dropdown-toggle#logout.focus {
	color: #333;
	background-color: #d4d4d4;
	border-color: #8c8c8c;
	}
	span#login_widget > .button:active,
	#logout:active,
	span#login_widget > .button.active,
	#logout.active,
	.open > .dropdown-togglespan#login_widget > .button,
	.open > .dropdown-toggle#logout {
	background-image: none;
	}
	span#login_widget > .button.disabled:hover,
	#logout.disabled:hover,
	span#login_widget > .button[disabled]:hover,
	#logout[disabled]:hover,
	fieldset[disabled] span#login_widget > .button:hover,
	fieldset[disabled] #logout:hover,
	span#login_widget > .button.disabled:focus,
	#logout.disabled:focus,
	span#login_widget > .button[disabled]:focus,
	#logout[disabled]:focus,
	fieldset[disabled] span#login_widget > .button:focus,
	fieldset[disabled] #logout:focus,
	span#login_widget > .button.disabled.focus,
	#logout.disabled.focus,
	span#login_widget > .button[disabled].focus,
	#logout[disabled].focus,
	fieldset[disabled] span#login_widget > .button.focus,
	fieldset[disabled] #logout.focus {
	background-color: #fff;
	border-color: #ccc;
	}
	span#login_widget > .button .badge,
	#logout .badge {
	color: #fff;
	background-color: #333;
	}
	.nav-header {
	text-transform: none;
	}
	#header > span {
	margin-top: 10px;
	}
	.modal_stretch .modal-dialog {
	/* Old browsers */
	display: -webkit-box;
	-webkit-box-orient: vertical;
	-webkit-box-align: stretch;
	display: -moz-box;
	-moz-box-orient: vertical;
	-moz-box-align: stretch;
	display: box;
	box-orient: vertical;
	box-align: stretch;
	/* Modern browsers */
	display: flex;
	flex-direction: column;
	align-items: stretch;
	min-height: 80vh;
	}
	.modal_stretch .modal-dialog .modal-body {
	max-height: calc(100vh - 200px);
	overflow: auto;
	flex: 1;
	}
	@media (min-width: 768px) {
	.modal .modal-dialog {
	width: 700px;
	}
	}
	@media (min-width: 768px) {
	select.form-control {
	margin-left: 12px;
	margin-right: 12px;
	}
	}
	/*!
	*
	* IPython auth
	*
	*/
	.center-nav {
	display: inline-block;
	margin-bottom: -4px;
	}
	/*!
	*
	* IPython tree view
	*
	*/
	/* We need an invisible input field on top of the sentense*/
	/* "Drag file onto the list ..." */
	.alternate_upload {
	background-color: none;
	display: inline;
	}
	.alternate_upload.form {
	padding: 0;
	margin: 0;
	}
	.alternate_upload input.fileinput {
	text-align: center;
	vertical-align: middle;
	display: inline;
	opacity: 0;
	z-index: 2;
	width: 12ex;
	margin-right: -12ex;
	}
	.alternate_upload .btn-upload {
	height: 22px;
	}
	/**
	* Primary styles
	*
	* Author: Jupyter Development Team
	*/
	[dir="rtl"] #tabs li {
	float: right;
	}
	ul#tabs {
	margin-bottom: 4px;
	}
	[dir="rtl"] ul#tabs {
	margin-right: 0px;
	}
	ul#tabs a {
	padding-top: 6px;
	padding-bottom: 4px;
	}
	ul.breadcrumb a:focus,
	ul.breadcrumb a:hover {
	text-decoration: none;
	}
	ul.breadcrumb i.icon-home {
	font-size: 16px;
	margin-right: 4px;
	}
	ul.breadcrumb span {
	color: #5e5e5e;
	}
	.list_toolbar {
	padding: 4px 0 4px 0;
	vertical-align: middle;
	}
	.list_toolbar .tree-buttons {
	padding-top: 1px;
	}
	[dir="rtl"] .list_toolbar .tree-buttons {
	float: left !important;
	}
	[dir="rtl"] .list_toolbar .pull-right {
	padding-top: 1px;
	float: left !important;
	}
	[dir="rtl"] .list_toolbar .pull-left {
	float: right !important;
	}
	.dynamic-buttons {
	padding-top: 3px;
	display: inline-block;
	}
	.list_toolbar [class*="span"] {
	min-height: 24px;
	}
	.list_header {
	font-weight: bold;
	background-color: #EEE;
	}
	.list_placeholder {
	font-weight: bold;
	padding-top: 4px;
	padding-bottom: 4px;
	padding-left: 7px;
	padding-right: 7px;
	}
	.list_container {
	margin-top: 4px;
	margin-bottom: 20px;
	border: 1px solid #ddd;
	border-radius: 2px;
	}
	.list_container > div {
	border-bottom: 1px solid #ddd;
	}
	.list_container > div:hover .list-item {
	background-color: red;
	}
	.list_container > div:last-child {
	border: none;
	}
	.list_item:hover .list_item {
	background-color: #ddd;
	}
	.list_item a {
	text-decoration: none;
	}
	.list_item:hover {
	background-color: #fafafa;
	}
	.list_header > div,
	.list_item > div {
	padding-top: 4px;
	padding-bottom: 4px;
	padding-left: 7px;
	padding-right: 7px;
	line-height: 22px;
	}
	.list_header > div input,
	.list_item > div input {
	margin-right: 7px;
	margin-left: 14px;
	vertical-align: baseline;
	line-height: 22px;
	position: relative;
	top: -1px;
	}
	.list_header > div .item_link,
	.list_item > div .item_link {
	margin-left: -1px;
	vertical-align: baseline;
	line-height: 22px;
	}
	.new-file input[type=checkbox] {
	visibility: hidden;
	}
	.item_name {
	line-height: 22px;
	height: 24px;
	}
	.item_icon {
	font-size: 14px;
	color: #5e5e5e;
	margin-right: 7px;
	margin-left: 7px;
	line-height: 22px;
	vertical-align: baseline;
	}
	.item_buttons {
	line-height: 1em;
	margin-left: -5px;
	}
	.item_buttons .btn,
	.item_buttons .btn-group,
	.item_buttons .input-group {
	float: left;
	}
	.item_buttons > .btn,
	.item_buttons > .btn-group,
	.item_buttons > .input-group {
	margin-left: 5px;
	}
	.item_buttons .btn {
	min-width: 13ex;
	}
	.item_buttons .running-indicator {
	padding-top: 4px;
	color: #5cb85c;
	}
	.item_buttons .kernel-name {
	padding-top: 4px;
	color: #5bc0de;
	margin-right: 7px;
	float: left;
	}
	.toolbar_info {
	height: 24px;
	line-height: 24px;
	}
	.list_item input:not([type=checkbox]) {
	padding-top: 3px;
	padding-bottom: 3px;
	height: 22px;
	line-height: 14px;
	margin: 0px;
	}
	.highlight_text {
	color: blue;
	}
	#project_name {
	display: inline-block;
	padding-left: 7px;
	margin-left: -2px;
	}
	#project_name > .breadcrumb {
	padding: 0px;
	margin-bottom: 0px;
	background-color: transparent;
	font-weight: bold;
	}
	#tree-selector {
	padding-right: 0px;
	}
	[dir="rtl"] #tree-selector a {
	float: right;
	}
	#button-select-all {
	min-width: 50px;
	}
	#select-all {
	margin-left: 7px;
	margin-right: 2px;
	}
	.menu_icon {
	margin-right: 2px;
	}
	.tab-content .row {
	margin-left: 0px;
	margin-right: 0px;
	}
	.folder_icon:before {
	display: inline-block;
	font: normal normal normal 14px/1 FontAwesome;
	font-size: inherit;
	text-rendering: auto;
	-webkit-font-smoothing: antialiased;
	-moz-osx-font-smoothing: grayscale;
	content: "\f114";
	}
	.folder_icon:before.pull-left {
	margin-right: .3em;
	}
	.folder_icon:before.pull-right {
	margin-left: .3em;
	}
	.notebook_icon:before {
	display: inline-block;
	font: normal normal normal 14px/1 FontAwesome;
	font-size: inherit;
	text-rendering: auto;
	-webkit-font-smoothing: antialiased;
	-moz-osx-font-smoothing: grayscale;
	content: "\f02d";
	position: relative;
	top: -1px;
	}
	.notebook_icon:before.pull-left {
	margin-right: .3em;
	}
	.notebook_icon:before.pull-right {
	margin-left: .3em;
	}
	.running_notebook_icon:before {
	display: inline-block;
	font: normal normal normal 14px/1 FontAwesome;
	font-size: inherit;
	text-rendering: auto;
	-webkit-font-smoothing: antialiased;
	-moz-osx-font-smoothing: grayscale;
	content: "\f02d";
	position: relative;
	top: -1px;
	color: #5cb85c;
	}
	.running_notebook_icon:before.pull-left {
	margin-right: .3em;
	}
	.running_notebook_icon:before.pull-right {
	margin-left: .3em;
	}
	.file_icon:before {
	display: inline-block;
	font: normal normal normal 14px/1 FontAwesome;
	font-size: inherit;
	text-rendering: auto;
	-webkit-font-smoothing: antialiased;
	-moz-osx-font-smoothing: grayscale;
	content: "\f016";
	position: relative;
	top: -2px;
	}
	.file_icon:before.pull-left {
	margin-right: .3em;
	}
	.file_icon:before.pull-right {
	margin-left: .3em;
	}
	#notebook_toolbar .pull-right {
	padding-top: 0px;
	margin-right: -1px;
	}
	ul#new-menu {
	left: auto;
	right: 0;
	}
	[dir="rtl"] #new-menu {
	text-align: right;
	}
	.kernel-menu-icon {
	padding-right: 12px;
	width: 24px;
	content: "\f096";
	}
	.kernel-menu-icon:before {
	content: "\f096";
	}
	.kernel-menu-icon-current:before {
	content: "\f00c";
	}
	#tab_content {
	padding-top: 20px;
	}
	#running .panel-group .panel {
	margin-top: 3px;
	margin-bottom: 1em;
	}
	#running .panel-group .panel .panel-heading {
	background-color: #EEE;
	padding-top: 4px;
	padding-bottom: 4px;
	padding-left: 7px;
	padding-right: 7px;
	line-height: 22px;
	}
	#running .panel-group .panel .panel-heading a:focus,
	#running .panel-group .panel .panel-heading a:hover {
	text-decoration: none;
	}
	#running .panel-group .panel .panel-body {
	padding: 0px;
	}
	#running .panel-group .panel .panel-body .list_container {
	margin-top: 0px;
	margin-bottom: 0px;
	border: 0px;
	border-radius: 0px;
	}
	#running .panel-group .panel .panel-body .list_container .list_item {
	border-bottom: 1px solid #ddd;
	}
	#running .panel-group .panel .panel-body .list_container .list_item:last-child {
	border-bottom: 0px;
	}
	[dir="rtl"] #running .col-sm-8 {
	float: right !important;
	}
	.delete-button {
	display: none;
	}
	.duplicate-button {
	display: none;
	}
	.rename-button {
	display: none;
	}
	.shutdown-button {
	display: none;
	}
	.dynamic-instructions {
	display: inline-block;
	padding-top: 4px;
	}
	/*!
	*
	* IPython text editor webapp
	*
	*/
	.selected-keymap i.fa {
	padding: 0px 5px;
	}
	.selected-keymap i.fa:before {
	content: "\f00c";
	}
	#mode-menu {
	overflow: auto;
	max-height: 20em;
	}
	.edit_app #header {
	-webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
	box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
	}
	.edit_app #menubar .navbar {
	/* Use a negative 1 bottom margin, so the border overlaps the border of the
	header */
	margin-bottom: -1px;
	}
	.dirty-indicator {
	display: inline-block;
	font: normal normal normal 14px/1 FontAwesome;
	font-size: inherit;
	text-rendering: auto;
	-webkit-font-smoothing: antialiased;
	-moz-osx-font-smoothing: grayscale;
	width: 20px;
	}
	.dirty-indicator.pull-left {
	margin-right: .3em;
	}
	.dirty-indicator.pull-right {
	margin-left: .3em;
	}
	.dirty-indicator-dirty {
	display: inline-block;
	font: normal normal normal 14px/1 FontAwesome;
	font-size: inherit;
	text-rendering: auto;
	-webkit-font-smoothing: antialiased;
	-moz-osx-font-smoothing: grayscale;
	width: 20px;
	}
	.dirty-indicator-dirty.pull-left {
	margin-right: .3em;
	}
	.dirty-indicator-dirty.pull-right {
	margin-left: .3em;
	}
	.dirty-indicator-clean {
	display: inline-block;
	font: normal normal normal 14px/1 FontAwesome;
	font-size: inherit;
	text-rendering: auto;
	-webkit-font-smoothing: antialiased;
	-moz-osx-font-smoothing: grayscale;
	width: 20px;
	}
	.dirty-indicator-clean.pull-left {
	margin-right: .3em;
	}
	.dirty-indicator-clean.pull-right {
	margin-left: .3em;
	}
	.dirty-indicator-clean:before {
	display: inline-block;
	font: normal normal normal 14px/1 FontAwesome;
	font-size: inherit;
	text-rendering: auto;
	-webkit-font-smoothing: antialiased;
	-moz-osx-font-smoothing: grayscale;
	content: "\f00c";
	}
	.dirty-indicator-clean:before.pull-left {
	margin-right: .3em;
	}
	.dirty-indicator-clean:before.pull-right {
	margin-left: .3em;
	}
	#filename {
	font-size: 16pt;
	display: table;
	padding: 0px 5px;
	}
	#current-mode {
	padding-left: 5px;
	padding-right: 5px;
	}
	#texteditor-backdrop {
	padding-top: 20px;
	padding-bottom: 20px;
	}
	@media not print {
	#texteditor-backdrop {
	background-color: #EEE;
	}
	}
	@media print {
	#texteditor-backdrop #texteditor-container .CodeMirror-gutter,
	#texteditor-backdrop #texteditor-container .CodeMirror-gutters {
	background-color: #fff;
	}
	}
	@media not print {
	#texteditor-backdrop #texteditor-container .CodeMirror-gutter,
	#texteditor-backdrop #texteditor-container .CodeMirror-gutters {
	background-color: #fff;
	}
	}
	@media not print {
	#texteditor-backdrop #texteditor-container {
	padding: 0px;
	background-color: #fff;
	-webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
	box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
	}
	}
	/*!
	*
	* IPython notebook
	*
	*/
	/* CSS font colors for translated ANSI colors. */
	.ansibold {
	font-weight: bold;
	}
	/* use dark versions for foreground, to improve visibility */
	.ansiblack {
	color: black;
	}
	.ansired {
	color: darkred;
	}
	.ansigreen {
	color: darkgreen;
	}
	.ansiyellow {
	color: #c4a000;
	}
	.ansiblue {
	color: darkblue;
	}
	.ansipurple {
	color: darkviolet;
	}
	.ansicyan {
	color: steelblue;
	}
	.ansigray {
	color: gray;
	}
	/* and light for background, for the same reason */
	.ansibgblack {
	background-color: black;
	}
	.ansibgred {
	background-color: red;
	}
	.ansibggreen {
	background-color: green;
	}
	.ansibgyellow {
	background-color: yellow;
	}
	.ansibgblue {
	background-color: blue;
	}
	.ansibgpurple {
	background-color: magenta;
	}
	.ansibgcyan {
	background-color: cyan;
	}
	.ansibggray {
	background-color: gray;
	}
	div.cell {
	/* Old browsers */
	display: -webkit-box;
	-webkit-box-orient: vertical;
	-webkit-box-align: stretch;
	display: -moz-box;
	-moz-box-orient: vertical;
	-moz-box-align: stretch;
	display: box;
	box-orient: vertical;
	box-align: stretch;
	/* Modern browsers */
	display: flex;
	flex-direction: column;
	align-items: stretch;
	border-radius: 2px;
	box-sizing: border-box;
	-moz-box-sizing: border-box;
	-webkit-box-sizing: border-box;
	border-width: 1px;
	border-style: solid;
	border-color: transparent;
	width: 100%;
	padding: 5px;
	/* This acts as a spacer between cells, that is outside the border */
	margin: 0px;
	outline: none;
	border-left-width: 1px;
	padding-left: 5px;
	background: linear-gradient(to right, transparent -40px, transparent 1px, transparent 1px, transparent 100%);
	}
	div.cell.jupyter-soft-selected {
	border-left-color: #90CAF9;
	border-left-color: #E3F2FD;
	border-left-width: 1px;
	padding-left: 5px;
	border-right-color: #E3F2FD;
	border-right-width: 1px;
	background: #E3F2FD;
	}
	@media print {
	div.cell.jupyter-soft-selected {
	border-color: transparent;
	}
	}
	div.cell.selected {
	border-color: #ababab;
	border-left-width: 0px;
	padding-left: 6px;
	background: linear-gradient(to right, #42A5F5 -40px, #42A5F5 5px, transparent 5px, transparent 100%);
	}
	@media print {
	div.cell.selected {
	border-color: transparent;
	}
	}
	div.cell.selected.jupyter-soft-selected {
	border-left-width: 0;
	padding-left: 6px;
	background: linear-gradient(to right, #42A5F5 -40px, #42A5F5 7px, #E3F2FD 7px, #E3F2FD 100%);
	}
	.edit_mode div.cell.selected {
	border-color: #66BB6A;
	border-left-width: 0px;
	padding-left: 6px;
	background: linear-gradient(to right, #66BB6A -40px, #66BB6A 5px, transparent 5px, transparent 100%);
	}
	@media print {
	.edit_mode div.cell.selected {
	border-color: transparent;
	}
	}
	.prompt {
	/* This needs to be wide enough for 3 digit prompt numbers: In[100]: */
	min-width: 14ex;
	/* This padding is tuned to match the padding on the CodeMirror editor. */
	padding: 0.4em;
	margin: 0px;
	font-family: monospace;
	text-align: right;
	/* This has to match that of the the CodeMirror class line-height below */
	line-height: 1.21429em;
	/* Don't highlight prompt number selection */
	-webkit-touch-callout: none;
	-webkit-user-select: none;
	-khtml-user-select: none;
	-moz-user-select: none;
	-ms-user-select: none;
	user-select: none;
	/* Use default cursor */
	cursor: default;
	}
	@media (max-width: 540px) {
	.prompt {
	text-align: left;
	}
	}
	div.inner_cell {
	min-width: 0;
	/* Old browsers */
	display: -webkit-box;
	-webkit-box-orient: vertical;
	-webkit-box-align: stretch;
	display: -moz-box;
	-moz-box-orient: vertical;
	-moz-box-align: stretch;
	display: box;
	box-orient: vertical;
	box-align: stretch;
	/* Modern browsers */
	display: flex;
	flex-direction: column;
	align-items: stretch;
	/* Old browsers */
	-webkit-box-flex: 1;
	-moz-box-flex: 1;
	box-flex: 1;
	/* Modern browsers */
	flex: 1;
	}
	/* input_area and input_prompt must match in top border and margin for alignment */
	div.input_area {
	border: 1px solid #cfcfcf;
	border-radius: 2px;
	background: #f7f7f7;
	line-height: 1.21429em;
	}
	/* This is needed so that empty prompt areas can collapse to zero height when there
	is no content in the output_subarea and the prompt. The main purpose of this is
	to make sure that empty JavaScript output_subareas have no height. */
	div.prompt:empty {
	padding-top: 0;
	padding-bottom: 0;
	}
	div.unrecognized_cell {
	padding: 5px 5px 5px 0px;
	/* Old browsers */
	display: -webkit-box;
	-webkit-box-orient: horizontal;
	-webkit-box-align: stretch;
	display: -moz-box;
	-moz-box-orient: horizontal;
	-moz-box-align: stretch;
	display: box;
	box-orient: horizontal;
	box-align: stretch;
	/* Modern browsers */
	display: flex;
	flex-direction: row;
	align-items: stretch;
	}
	div.unrecognized_cell .inner_cell {
	border-radius: 2px;
	padding: 5px;
	font-weight: bold;
	color: red;
	border: 1px solid #cfcfcf;
	background: #eaeaea;
	}
	div.unrecognized_cell .inner_cell a {
	color: inherit;
	text-decoration: none;
	}
	div.unrecognized_cell .inner_cell a:hover {
	color: inherit;
	text-decoration: none;
	}
	@media (max-width: 540px) {
	div.unrecognized_cell > div.prompt {
	display: none;
	}
	}
	div.code_cell {
	/* avoid page breaking on code cells when printing */
	}
	@media print {
	div.code_cell {
	page-break-inside: avoid;
	}
	}
	/* any special styling for code cells that are currently running goes here */
	div.input {
	page-break-inside: avoid;
	/* Old browsers */
	display: -webkit-box;
	-webkit-box-orient: horizontal;
	-webkit-box-align: stretch;
	display: -moz-box;
	-moz-box-orient: horizontal;
	-moz-box-align: stretch;
	display: box;
	box-orient: horizontal;
	box-align: stretch;
	/* Modern browsers */
	display: flex;
	flex-direction: row;
	align-items: stretch;
	}
	@media (max-width: 540px) {
	div.input {
	/* Old browsers */
	display: -webkit-box;
	-webkit-box-orient: vertical;
	-webkit-box-align: stretch;
	display: -moz-box;
	-moz-box-orient: vertical;
	-moz-box-align: stretch;
	display: box;
	box-orient: vertical;
	box-align: stretch;
	/* Modern browsers */
	display: flex;
	flex-direction: column;
	align-items: stretch;
	}
	}
	/* input_area and input_prompt must match in top border and margin for alignment */
	div.input_prompt {
	color: #303F9F;
	border-top: 1px solid transparent;
	}
	div.input_area > div.highlight {
	margin: 0.4em;
	border: none;
	padding: 0px;
	background-color: transparent;
	}
	div.input_area > div.highlight > pre {
	margin: 0px;
	border: none;
	padding: 0px;
	background-color: transparent;
	}
	/* The following gets added to the <head> if it is detected that the user has a
	* monospace font with inconsistent normal/bold/italic height. See
	* notebookmain.js. Such fonts will have keywords vertically offset with
	* respect to the rest of the text. The user should select a better font.
	* See: https://github.com/ipython/ipython/issues/1503
	*
	* .CodeMirror span {
	* vertical-align: bottom;
	* }
	*/
	.CodeMirror {
	line-height: 1.21429em;
	/* Changed from 1em to our global default */
	font-size: 14px;
	height: auto;
	/* Changed to auto to autogrow */
	background: none;
	/* Changed from white to allow our bg to show through */
	}
	.CodeMirror-scroll {
	/* The CodeMirror docs are a bit fuzzy on if overflow-y should be hidden or visible.*/
	/* We have found that if it is visible, vertical scrollbars appear with font size changes.*/
	overflow-y: hidden;
	overflow-x: auto;
	}
	.CodeMirror-lines {
	/* In CM2, this used to be 0.4em, but in CM3 it went to 4px. We need the em value because */
	/* we have set a different line-height and want this to scale with that. */
	padding: 0.4em;
	}
	.CodeMirror-linenumber {
	padding: 0 8px 0 4px;
	}
	.CodeMirror-gutters {
	border-bottom-left-radius: 2px;
	border-top-left-radius: 2px;
	}
	.CodeMirror pre {
	/* In CM3 this went to 4px from 0 in CM2. We need the 0 value because of how we size */
	/* .CodeMirror-lines */
	padding: 0;
	border: 0;
	border-radius: 0;
	}
	/*

	Original style from softwaremaniacs.org (c) Ivan Sagalaev <Maniac@SoftwareManiacs.Org>
	Adapted from GitHub theme

	*/
	.highlight-base {
	color: #000;
	}
	.highlight-variable {
	color: #000;
	}
	.highlight-variable-2 {
	color: #1a1a1a;
	}
	.highlight-variable-3 {
	color: #333333;
	}
	.highlight-string {
	color: #BA2121;
	}
	.highlight-comment {
	color: #408080;
	font-style: italic;
	}
	.highlight-number {
	color: #080;
	}
	.highlight-atom {
	color: #88F;
	}
	.highlight-keyword {
	color: #008000;
	font-weight: bold;
	}
	.highlight-builtin {
	color: #008000;
	}
	.highlight-error {
	color: #f00;
	}
	.highlight-operator {
	color: #AA22FF;
	font-weight: bold;
	}
	.highlight-meta {
	color: #AA22FF;
	}
	/* previously not defined, copying from default codemirror */
	.highlight-def {
	color: #00f;
	}
	.highlight-string-2 {
	color: #f50;
	}
	.highlight-qualifier {
	color: #555;
	}
	.highlight-bracket {
	color: #997;
	}
	.highlight-tag {
	color: #170;
	}
	.highlight-attribute {
	color: #00c;
	}
	.highlight-header {
	color: blue;
	}
	.highlight-quote {
	color: #090;
	}
	.highlight-link {
	color: #00c;
	}
	/* apply the same style to codemirror */
	.cm-s-ipython span.cm-keyword {
	color: #008000;
	font-weight: bold;
	}
	.cm-s-ipython span.cm-atom {
	color: #88F;
	}
	.cm-s-ipython span.cm-number {
	color: #080;
	}
	.cm-s-ipython span.cm-def {
	color: #00f;
	}
	.cm-s-ipython span.cm-variable {
	color: #000;
	}
	.cm-s-ipython span.cm-operator {
	color: #AA22FF;
	font-weight: bold;
	}
	.cm-s-ipython span.cm-variable-2 {
	color: #1a1a1a;
	}
	.cm-s-ipython span.cm-variable-3 {
	color: #333333;
	}
	.cm-s-ipython span.cm-comment {
	color: #408080;
	font-style: italic;
	}
	.cm-s-ipython span.cm-string {
	color: #BA2121;
	}
	.cm-s-ipython span.cm-string-2 {
	color: #f50;
	}
	.cm-s-ipython span.cm-meta {
	color: #AA22FF;
	}
	.cm-s-ipython span.cm-qualifier {
	color: #555;
	}
	.cm-s-ipython span.cm-builtin {
	color: #008000;
	}
	.cm-s-ipython span.cm-bracket {
	color: #997;
	}
	.cm-s-ipython span.cm-tag {
	color: #170;
	}
	.cm-s-ipython span.cm-attribute {
	color: #00c;
	}
	.cm-s-ipython span.cm-header {
	color: blue;
	}
	.cm-s-ipython span.cm-quote {
	color: #090;
	}
	.cm-s-ipython span.cm-link {
	color: #00c;
	}
	.cm-s-ipython span.cm-error {
	color: #f00;
	}
	.cm-s-ipython span.cm-tab {
	background: url(data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAADAAAAAMCAYAAAAkuj5RAAAAAXNSR0IArs4c6QAAAGFJREFUSMft1LsRQFAQheHPowAKoACx3IgEKtaEHujDjORSgWTH/ZOdnZOcM/sgk/kFFWY0qV8foQwS4MKBCS3qR6ixBJvElOobYAtivseIE120FaowJPN75GMu8j/LfMwNjh4HUpwg4LUAAAAASUVORK5CYII=);
	background-position: right;
	background-repeat: no-repeat;
	}
	div.output_wrapper {
	/* this position must be relative to enable descendents to be absolute within it */
	position: relative;
	/* Old browsers */
	display: -webkit-box;
	-webkit-box-orient: vertical;
	-webkit-box-align: stretch;
	display: -moz-box;
	-moz-box-orient: vertical;
	-moz-box-align: stretch;
	display: box;
	box-orient: vertical;
	box-align: stretch;
	/* Modern browsers */
	display: flex;
	flex-direction: column;
	align-items: stretch;
	z-index: 1;
	}
	/* class for the output area when it should be height-limited */
	div.output_scroll {
	/* ideally, this would be max-height, but FF barfs all over that */
	height: 24em;
	/* FF needs this and the wrapper to specify full width, or it will shrinkwrap */
	width: 100%;
	overflow: auto;
	border-radius: 2px;
	-webkit-box-shadow: inset 0 2px 8px rgba(0, 0, 0, 0.8);
	box-shadow: inset 0 2px 8px rgba(0, 0, 0, 0.8);
	display: block;
	}
	/* output div while it is collapsed */
	div.output_collapsed {
	margin: 0px;
	padding: 0px;
	/* Old browsers */
	display: -webkit-box;
	-webkit-box-orient: vertical;
	-webkit-box-align: stretch;
	display: -moz-box;
	-moz-box-orient: vertical;
	-moz-box-align: stretch;
	display: box;
	box-orient: vertical;
	box-align: stretch;
	/* Modern browsers */
	display: flex;
	flex-direction: column;
	align-items: stretch;
	}
	div.out_prompt_overlay {
	height: 100%;
	padding: 0px 0.4em;
	position: absolute;
	border-radius: 2px;
	}
	div.out_prompt_overlay:hover {
	/* use inner shadow to get border that is computed the same on WebKit/FF */
	-webkit-box-shadow: inset 0 0 1px #000;
	box-shadow: inset 0 0 1px #000;
	background: rgba(240, 240, 240, 0.5);
	}
	div.output_prompt {
	color: #D84315;
	}
	/* This class is the outer container of all output sections. */
	div.output_area {
	padding: 0px;
	page-break-inside: avoid;
	/* Old browsers */
	display: -webkit-box;
	-webkit-box-orient: horizontal;
	-webkit-box-align: stretch;
	display: -moz-box;
	-moz-box-orient: horizontal;
	-moz-box-align: stretch;
	display: box;
	box-orient: horizontal;
	box-align: stretch;
	/* Modern browsers */
	display: flex;
	flex-direction: row;
	align-items: stretch;
	}
	div.output_area .MathJax_Display {
	text-align: left !important;
	}
	div.output_area .rendered_html table {
	margin-left: 0;
	margin-right: 0;
	}
	div.output_area .rendered_html img {
	margin-left: 0;
	margin-right: 0;
	}
	div.output_area img,
	div.output_area svg {
	max-width: 100%;
	height: auto;
	}
	div.output_area img.unconfined,
	div.output_area svg.unconfined {
	max-width: none;
	}
	/* This is needed to protect the pre formating from global settings such
	as that of bootstrap */
	.output {
	/* Old browsers */
	display: -webkit-box;
	-webkit-box-orient: vertical;
	-webkit-box-align: stretch;
	display: -moz-box;
	-moz-box-orient: vertical;
	-moz-box-align: stretch;
	display: box;
	box-orient: vertical;
	box-align: stretch;
	/* Modern browsers */
	display: flex;
	flex-direction: column;
	align-items: stretch;
	}
	@media (max-width: 540px) {
	div.output_area {
	/* Old browsers */
	display: -webkit-box;
	-webkit-box-orient: vertical;
	-webkit-box-align: stretch;
	display: -moz-box;
	-moz-box-orient: vertical;
	-moz-box-align: stretch;
	display: box;
	box-orient: vertical;
	box-align: stretch;
	/* Modern browsers */
	display: flex;
	flex-direction: column;
	align-items: stretch;
	}
	}
	div.output_area pre {
	margin: 0;
	padding: 0;
	border: 0;
	vertical-align: baseline;
	color: black;
	background-color: transparent;
	border-radius: 0;
	}
	/* This class is for the output subarea inside the output_area and after
	the prompt div. */
	div.output_subarea {
	overflow-x: auto;
	padding: 0.4em;
	/* Old browsers */
	-webkit-box-flex: 1;
	-moz-box-flex: 1;
	box-flex: 1;
	/* Modern browsers */
	flex: 1;
	max-width: calc(100% - 14ex);
	}
	div.output_scroll div.output_subarea {
	overflow-x: visible;
	}
	/* The rest of the output_* classes are for special styling of the different
	output types */
	/* all text output has this class: */
	div.output_text {
	text-align: left;
	color: #000;
	/* This has to match that of the the CodeMirror class line-height below */
	line-height: 1.21429em;
	}
	/* stdout/stderr are 'text' as well as 'stream', but execute_result/error are not streams */
	div.output_stderr {
	background: #fdd;
	/* very light red background for stderr */
	}
	div.output_latex {
	text-align: left;
	}
	/* Empty output_javascript divs should have no height */
	div.output_javascript:empty {
	padding: 0;
	}
	.js-error {
	color: darkred;
	}
	/* raw_input styles */
	div.raw_input_container {
	line-height: 1.21429em;
	padding-top: 5px;
	}
	pre.raw_input_prompt {
	/* nothing needed here. */
	}
	input.raw_input {
	font-family: monospace;
	font-size: inherit;
	color: inherit;
	width: auto;
	/* make sure input baseline aligns with prompt */
	vertical-align: baseline;
	/* padding + margin = 0.5em between prompt and cursor */
	padding: 0em 0.25em;
	margin: 0em 0.25em;
	}
	input.raw_input:focus {
	box-shadow: none;
	}
	p.p-space {
	margin-bottom: 10px;
	}
	div.output_unrecognized {
	padding: 5px;
	font-weight: bold;
	color: red;
	}
	div.output_unrecognized a {
	color: inherit;
	text-decoration: none;
	}
	div.output_unrecognized a:hover {
	color: inherit;
	text-decoration: none;
	}
	.rendered_html {
	color: #000;
	/* any extras will just be numbers: */
	}
	.rendered_html em {
	font-style: italic;
	}
	.rendered_html strong {
	font-weight: bold;
	}
	.rendered_html u {
	text-decoration: underline;
	}
	.rendered_html :link {
	text-decoration: underline;
	}
	.rendered_html :visited {
	text-decoration: underline;
	}
	.rendered_html h1 {
	font-size: 185.7%;
	margin: 1.08em 0 0 0;
	font-weight: bold;
	line-height: 1.0;
	}
	.rendered_html h2 {
	font-size: 157.1%;
	margin: 1.27em 0 0 0;
	font-weight: bold;
	line-height: 1.0;
	}
	.rendered_html h3 {
	font-size: 128.6%;
	margin: 1.55em 0 0 0;
	font-weight: bold;
	line-height: 1.0;
	}
	.rendered_html h4 {
	font-size: 100%;
	margin: 2em 0 0 0;
	font-weight: bold;
	line-height: 1.0;
	}
	.rendered_html h5 {
	font-size: 100%;
	margin: 2em 0 0 0;
	font-weight: bold;
	line-height: 1.0;
	font-style: italic;
	}
	.rendered_html h6 {
	font-size: 100%;
	margin: 2em 0 0 0;
	font-weight: bold;
	line-height: 1.0;
	font-style: italic;
	}
	.rendered_html h1:first-child {
	margin-top: 0.538em;
	}
	.rendered_html h2:first-child {
	margin-top: 0.636em;
	}
	.rendered_html h3:first-child {
	margin-top: 0.777em;
	}
	.rendered_html h4:first-child {
	margin-top: 1em;
	}
	.rendered_html h5:first-child {
	margin-top: 1em;
	}
	.rendered_html h6:first-child {
	margin-top: 1em;
	}
	.rendered_html ul {
	list-style: disc;
	margin: 0em 2em;
	padding-left: 0px;
	}
	.rendered_html ul ul {
	list-style: square;
	margin: 0em 2em;
	}
	.rendered_html ul ul ul {
	list-style: circle;
	margin: 0em 2em;
	}
	.rendered_html ol {
	list-style: decimal;
	margin: 0em 2em;
	padding-left: 0px;
	}
	.rendered_html ol ol {
	list-style: upper-alpha;
	margin: 0em 2em;
	}
	.rendered_html ol ol ol {
	list-style: lower-alpha;
	margin: 0em 2em;
	}
	.rendered_html ol ol ol ol {
	list-style: lower-roman;
	margin: 0em 2em;
	}
	.rendered_html ol ol ol ol ol {
	list-style: decimal;
	margin: 0em 2em;
	}
	.rendered_html * + ul {
	margin-top: 1em;
	}
	.rendered_html * + ol {
	margin-top: 1em;
	}
	.rendered_html hr {
	color: black;
	background-color: black;
	}
	.rendered_html pre {
	margin: 1em 2em;
	}
	.rendered_html pre,
	.rendered_html code {
	border: 0;
	background-color: #fff;
	color: #000;
	font-size: 100%;
	padding: 0px;
	}
	.rendered_html blockquote {
	margin: 1em 2em;
	}
	.rendered_html table {
	margin-left: auto;
	margin-right: auto;
	border: 1px solid black;
	border-collapse: collapse;
	}
	.rendered_html tr,
	.rendered_html th,
	.rendered_html td {
	border: 1px solid black;
	border-collapse: collapse;
	margin: 1em 2em;
	}
	.rendered_html td,
	.rendered_html th {
	text-align: left;
	vertical-align: middle;
	padding: 4px;
	}
	.rendered_html th {
	font-weight: bold;
	}
	.rendered_html * + table {
	margin-top: 1em;
	}
	.rendered_html p {
	text-align: left;
	}
	.rendered_html * + p {
	margin-top: 1em;
	}
	.rendered_html img {
	display: block;
	margin-left: auto;
	margin-right: auto;
	}
	.rendered_html * + img {
	margin-top: 1em;
	}
	.rendered_html img,
	.rendered_html svg {
	max-width: 100%;
	height: auto;
	}
	.rendered_html img.unconfined,
	.rendered_html svg.unconfined {
	max-width: none;
	}
	div.text_cell {
	/* Old browsers */
	display: -webkit-box;
	-webkit-box-orient: horizontal;
	-webkit-box-align: stretch;
	display: -moz-box;
	-moz-box-orient: horizontal;
	-moz-box-align: stretch;
	display: box;
	box-orient: horizontal;
	box-align: stretch;
	/* Modern browsers */
	display: flex;
	flex-direction: row;
	align-items: stretch;
	}
	@media (max-width: 540px) {
	div.text_cell > div.prompt {
	display: none;
	}
	}
	div.text_cell_render {
	/font-family: "Helvetica Neue", Arial, Helvetica, Geneva, sans-serif;/
	outline: none;
	resize: none;
	width: inherit;
	border-style: none;
	padding: 0.5em 0.5em 0.5em 0.4em;
	color: #000;
	box-sizing: border-box;
	-moz-box-sizing: border-box;
	-webkit-box-sizing: border-box;
	}
	a.anchor-link:link {
	text-decoration: none;
	padding: 0px 20px;
	visibility: hidden;
	}
	h1:hover .anchor-link,
	h2:hover .anchor-link,
	h3:hover .anchor-link,
	h4:hover .anchor-link,
	h5:hover .anchor-link,
	h6:hover .anchor-link {
	visibility: visible;
	}
	.text_cell.rendered .input_area {
	display: none;
	}
	.text_cell.rendered .rendered_html {
	overflow-x: auto;
	overflow-y: hidden;
	}
	.text_cell.unrendered .text_cell_render {
	display: none;
	}
	.cm-header-1,
	.cm-header-2,
	.cm-header-3,
	.cm-header-4,
	.cm-header-5,
	.cm-header-6 {
	font-weight: bold;
	font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
	}
	.cm-header-1 {
	font-size: 185.7%;
	}
	.cm-header-2 {
	font-size: 157.1%;
	}
	.cm-header-3 {
	font-size: 128.6%;
	}
	.cm-header-4 {
	font-size: 110%;
	}
	.cm-header-5 {
	font-size: 100%;
	font-style: italic;
	}
	.cm-header-6 {
	font-size: 100%;
	font-style: italic;
	}
	/*!
	*
	* IPython notebook webapp
	*
	*/
	@media (max-width: 767px) {
	.notebook_app {
	padding-left: 0px;
	padding-right: 0px;
	}
	}
	#ipython-main-app {
	box-sizing: border-box;
	-moz-box-sizing: border-box;
	-webkit-box-sizing: border-box;
	height: 100%;
	}
	div#notebook_panel {
	margin: 0px;
	padding: 0px;
	box-sizing: border-box;
	-moz-box-sizing: border-box;
	-webkit-box-sizing: border-box;
	height: 100%;
	}
	div#notebook {
	font-size: 14px;
	line-height: 20px;
	overflow-y: hidden;
	overflow-x: auto;
	width: 100%;
	/* This spaces the page away from the edge of the notebook area */
	padding-top: 20px;
	margin: 0px;
	outline: none;
	box-sizing: border-box;
	-moz-box-sizing: border-box;
	-webkit-box-sizing: border-box;
	min-height: 100%;
	}
	@media not print {
	#notebook-container {
	padding: 15px;
	background-color: #fff;
	min-height: 0;
	-webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
	box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
	}
	}
	@media print {
	#notebook-container {
	width: 100%;
	}
	}
	div.ui-widget-content {
	border: 1px solid #ababab;
	outline: none;
	}
	pre.dialog {
	background-color: #f7f7f7;
	border: 1px solid #ddd;
	border-radius: 2px;
	padding: 0.4em;
	padding-left: 2em;
	}
	p.dialog {
	padding: 0.2em;
	}
	/* Word-wrap output correctly. This is the CSS3 spelling, though Firefox seems
	to not honor it correctly. Webkit browsers (Chrome, rekonq, Safari) do.
	*/
	pre,
	code,
	kbd,
	samp {
	white-space: pre-wrap;
	}
	#fonttest {
	font-family: monospace;
	}
	p {
	margin-bottom: 0;
	}
	.end_space {
	min-height: 100px;
	transition: height .2s ease;
	}
	.notebook_app > #header {
	-webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
	box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
	}
	@media not print {
	.notebook_app {
	background-color: #EEE;
	}
	}
	kbd {
	border-style: solid;
	border-width: 1px;
	box-shadow: none;
	margin: 2px;
	padding-left: 2px;
	padding-right: 2px;
	padding-top: 1px;
	padding-bottom: 1px;
	}
	/* CSS for the cell toolbar */
	.celltoolbar {
	border: thin solid #CFCFCF;
	border-bottom: none;
	background: #EEE;
	border-radius: 2px 2px 0px 0px;
	width: 100%;
	height: 29px;
	padding-right: 4px;
	/* Old browsers */
	display: -webkit-box;
	-webkit-box-orient: horizontal;
	-webkit-box-align: stretch;
	display: -moz-box;
	-moz-box-orient: horizontal;
	-moz-box-align: stretch;
	display: box;
	box-orient: horizontal;
	box-align: stretch;
	/* Modern browsers */
	display: flex;
	flex-direction: row;
	align-items: stretch;
	/* Old browsers */
	-webkit-box-pack: end;
	-moz-box-pack: end;
	box-pack: end;
	/* Modern browsers */
	justify-content: flex-end;
	display: -webkit-flex;
	}
	@media print {
	.celltoolbar {
	display: none;
	}
	}
	.ctb_hideshow {
	display: none;
	vertical-align: bottom;
	}
	/* ctb_show is added to the ctb_hideshow div to show the cell toolbar.
	Cell toolbars are only shown when the ctb_global_show class is also set.
	*/
	.ctb_global_show .ctb_show.ctb_hideshow {
	display: block;
	}
	.ctb_global_show .ctb_show + .input_area,
	.ctb_global_show .ctb_show + div.text_cell_input,
	.ctb_global_show .ctb_show ~ div.text_cell_render {
	border-top-right-radius: 0px;
	border-top-left-radius: 0px;
	}
	.ctb_global_show .ctb_show ~ div.text_cell_render {
	border: 1px solid #cfcfcf;
	}
	.celltoolbar {
	font-size: 87%;
	padding-top: 3px;
	}
	.celltoolbar select {
	display: block;
	width: 100%;
	height: 32px;
	padding: 6px 12px;
	font-size: 13px;
	line-height: 1.42857143;
	color: #555555;
	background-color: #fff;
	background-image: none;
	border: 1px solid #ccc;
	border-radius: 2px;
	-webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
	box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
	-webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
	-o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
	transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
	height: 30px;
	padding: 5px 10px;
	font-size: 12px;
	line-height: 1.5;
	border-radius: 1px;
	width: inherit;
	font-size: inherit;
	height: 22px;
	padding: 0px;
	display: inline-block;
	}
	.celltoolbar select:focus {
	border-color: #66afe9;
	outline: 0;
	-webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
	box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
	}
	.celltoolbar select::-moz-placeholder {
	color: #999;
	opacity: 1;
	}
	.celltoolbar select:-ms-input-placeholder {
	color: #999;
	}
	.celltoolbar select::-webkit-input-placeholder {
	color: #999;
	}
	.celltoolbar select::-ms-expand {
	border: 0;
	background-color: transparent;
	}
	.celltoolbar select[disabled],
	.celltoolbar select[readonly],
	fieldset[disabled] .celltoolbar select {
	background-color: #eeeeee;
	opacity: 1;
	}
	.celltoolbar select[disabled],
	fieldset[disabled] .celltoolbar select {
	cursor: not-allowed;
	}
	textarea.celltoolbar select {
	height: auto;
	}
	select.celltoolbar select {
	height: 30px;
	line-height: 30px;
	}
	textarea.celltoolbar select,
	select[multiple].celltoolbar select {
	height: auto;
	}
	.celltoolbar label {
	margin-left: 5px;
	margin-right: 5px;
	}
	.completions {
	position: absolute;
	z-index: 110;
	overflow: hidden;
	border: 1px solid #ababab;
	border-radius: 2px;
	-webkit-box-shadow: 0px 6px 10px -1px #adadad;
	box-shadow: 0px 6px 10px -1px #adadad;
	line-height: 1;
	}
	.completions select {
	background: white;
	outline: none;
	border: none;
	padding: 0px;
	margin: 0px;
	overflow: auto;
	font-family: monospace;
	font-size: 110%;
	color: #000;
	width: auto;
	}
	.completions select option.context {
	color: #286090;
	}
	#kernel_logo_widget {
	float: right !important;
	float: right;
	}
	#kernel_logo_widget .current_kernel_logo {
	display: none;
	margin-top: -1px;
	margin-bottom: -1px;
	width: 32px;
	height: 32px;
	}
	#menubar {
	box-sizing: border-box;
	-moz-box-sizing: border-box;
	-webkit-box-sizing: border-box;
	margin-top: 1px;
	}
	#menubar .navbar {
	border-top: 1px;
	border-radius: 0px 0px 2px 2px;
	margin-bottom: 0px;
	}
	#menubar .navbar-toggle {
	float: left;
	padding-top: 7px;
	padding-bottom: 7px;
	border: none;
	}
	#menubar .navbar-collapse {
	clear: left;
	}
	.nav-wrapper {
	border-bottom: 1px solid #e7e7e7;
	}
	i.menu-icon {
	padding-top: 4px;
	}
	ul#help_menu li a {
	overflow: hidden;
	padding-right: 2.2em;
	}
	ul#help_menu li a i {
	margin-right: -1.2em;
	}
	.dropdown-submenu {
	position: relative;
	}
	.dropdown-submenu > .dropdown-menu {
	top: 0;
	left: 100%;
	margin-top: -6px;
	margin-left: -1px;
	}
	.dropdown-submenu:hover > .dropdown-menu {
	display: block;
	}
	.dropdown-submenu > a:after {
	display: inline-block;
	font: normal normal normal 14px/1 FontAwesome;
	font-size: inherit;
	text-rendering: auto;
	-webkit-font-smoothing: antialiased;
	-moz-osx-font-smoothing: grayscale;
	display: block;
	content: "\f0da";
	float: right;
	color: #333333;
	margin-top: 2px;
	margin-right: -10px;
	}
	.dropdown-submenu > a:after.pull-left {
	margin-right: .3em;
	}
	.dropdown-submenu > a:after.pull-right {
	margin-left: .3em;
	}
	.dropdown-submenu:hover > a:after {
	color: #262626;
	}
	.dropdown-submenu.pull-left {
	float: none;
	}
	.dropdown-submenu.pull-left > .dropdown-menu {
	left: -100%;
	margin-left: 10px;
	}
	#notification_area {
	float: right !important;
	float: right;
	z-index: 10;
	}
	.indicator_area {
	float: right !important;
	float: right;
	color: #777;
	margin-left: 5px;
	margin-right: 5px;
	width: 11px;
	z-index: 10;
	text-align: center;
	width: auto;
	}
	#kernel_indicator {
	float: right !important;
	float: right;
	color: #777;
	margin-left: 5px;
	margin-right: 5px;
	width: 11px;
	z-index: 10;
	text-align: center;
	width: auto;
	border-left: 1px solid;
	}
	#kernel_indicator .kernel_indicator_name {
	padding-left: 5px;
	padding-right: 5px;
	}
	#modal_indicator {
	float: right !important;
	float: right;
	color: #777;
	margin-left: 5px;
	margin-right: 5px;
	width: 11px;
	z-index: 10;
	text-align: center;
	width: auto;
	}
	#readonly-indicator {
	float: right !important;
	float: right;
	color: #777;
	margin-left: 5px;
	margin-right: 5px;
	width: 11px;
	z-index: 10;
	text-align: center;
	width: auto;
	margin-top: 2px;
	margin-bottom: 0px;
	margin-left: 0px;
	margin-right: 0px;
	display: none;
	}
	.modal_indicator:before {
	width: 1.28571429em;
	text-align: center;
	}
	.edit_mode .modal_indicator:before {
	display: inline-block;
	font: normal normal normal 14px/1 FontAwesome;
	font-size: inherit;
	text-rendering: auto;
	-webkit-font-smoothing: antialiased;
	-moz-osx-font-smoothing: grayscale;
	content: "\f040";
	}
	.edit_mode .modal_indicator:before.pull-left {
	margin-right: .3em;
	}
	.edit_mode .modal_indicator:before.pull-right {
	margin-left: .3em;
	}
	.command_mode .modal_indicator:before {
	display: inline-block;
	font: normal normal normal 14px/1 FontAwesome;
	font-size: inherit;
	text-rendering: auto;
	-webkit-font-smoothing: antialiased;
	-moz-osx-font-smoothing: grayscale;
	content: ' ';
	}
	.command_mode .modal_indicator:before.pull-left {
	margin-right: .3em;
	}
	.command_mode .modal_indicator:before.pull-right {
	margin-left: .3em;
	}
	.kernel_idle_icon:before {
	display: inline-block;
	font: normal normal normal 14px/1 FontAwesome;
	font-size: inherit;
	text-rendering: auto;
	-webkit-font-smoothing: antialiased;
	-moz-osx-font-smoothing: grayscale;
	content: "\f10c";
	}
	.kernel_idle_icon:before.pull-left {
	margin-right: .3em;
	}
	.kernel_idle_icon:before.pull-right {
	margin-left: .3em;
	}
	.kernel_busy_icon:before {
	display: inline-block;
	font: normal normal normal 14px/1 FontAwesome;
	font-size: inherit;
	text-rendering: auto;
	-webkit-font-smoothing: antialiased;
	-moz-osx-font-smoothing: grayscale;
	content: "\f111";
	}
	.kernel_busy_icon:before.pull-left {
	margin-right: .3em;
	}
	.kernel_busy_icon:before.pull-right {
	margin-left: .3em;
	}
	.kernel_dead_icon:before {
	display: inline-block;
	font: normal normal normal 14px/1 FontAwesome;
	font-size: inherit;
	text-rendering: auto;
	-webkit-font-smoothing: antialiased;
	-moz-osx-font-smoothing: grayscale;
	content: "\f1e2";
	}
	.kernel_dead_icon:before.pull-left {
	margin-right: .3em;
	}
	.kernel_dead_icon:before.pull-right {
	margin-left: .3em;
	}
	.kernel_disconnected_icon:before {
	display: inline-block;
	font: normal normal normal 14px/1 FontAwesome;
	font-size: inherit;
	text-rendering: auto;
	-webkit-font-smoothing: antialiased;
	-moz-osx-font-smoothing: grayscale;
	content: "\f127";
	}
	.kernel_disconnected_icon:before.pull-left {
	margin-right: .3em;
	}
	.kernel_disconnected_icon:before.pull-right {
	margin-left: .3em;
	}
	.notification_widget {
	color: #777;
	z-index: 10;
	background: rgba(240, 240, 240, 0.5);
	margin-right: 4px;
	color: #333;
	background-color: #fff;
	border-color: #ccc;
	}
	.notification_widget:focus,
	.notification_widget.focus {
	color: #333;
	background-color: #e6e6e6;
	border-color: #8c8c8c;
	}
	.notification_widget:hover {
	color: #333;
	background-color: #e6e6e6;
	border-color: #adadad;
	}
	.notification_widget:active,
	.notification_widget.active,
	.open > .dropdown-toggle.notification_widget {
	color: #333;
	background-color: #e6e6e6;
	border-color: #adadad;
	}
	.notification_widget:active:hover,
	.notification_widget.active:hover,
	.open > .dropdown-toggle.notification_widget:hover,
	.notification_widget:active:focus,
	.notification_widget.active:focus,
	.open > .dropdown-toggle.notification_widget:focus,
	.notification_widget:active.focus,
	.notification_widget.active.focus,
	.open > .dropdown-toggle.notification_widget.focus {
	color: #333;
	background-color: #d4d4d4;
	border-color: #8c8c8c;
	}
	.notification_widget:active,
	.notification_widget.active,
	.open > .dropdown-toggle.notification_widget {
	background-image: none;
	}
	.notification_widget.disabled:hover,
	.notification_widget[disabled]:hover,
	fieldset[disabled] .notification_widget:hover,
	.notification_widget.disabled:focus,
	.notification_widget[disabled]:focus,
	fieldset[disabled] .notification_widget:focus,
	.notification_widget.disabled.focus,
	.notification_widget[disabled].focus,
	fieldset[disabled] .notification_widget.focus {
	background-color: #fff;
	border-color: #ccc;
	}
	.notification_widget .badge {
	color: #fff;
	background-color: #333;
	}
	.notification_widget.warning {
	color: #fff;
	background-color: #f0ad4e;
	border-color: #eea236;
	}
	.notification_widget.warning:focus,
	.notification_widget.warning.focus {
	color: #fff;
	background-color: #ec971f;
	border-color: #985f0d;
	}
	.notification_widget.warning:hover {
	color: #fff;
	background-color: #ec971f;
	border-color: #d58512;
	}
	.notification_widget.warning:active,
	.notification_widget.warning.active,
	.open > .dropdown-toggle.notification_widget.warning {
	color: #fff;
	background-color: #ec971f;
	border-color: #d58512;
	}
	.notification_widget.warning:active:hover,
	.notification_widget.warning.active:hover,
	.open > .dropdown-toggle.notification_widget.warning:hover,
	.notification_widget.warning:active:focus,
	.notification_widget.warning.active:focus,
	.open > .dropdown-toggle.notification_widget.warning:focus,
	.notification_widget.warning:active.focus,
	.notification_widget.warning.active.focus,
	.open > .dropdown-toggle.notification_widget.warning.focus {
	color: #fff;
	background-color: #d58512;
	border-color: #985f0d;
	}
	.notification_widget.warning:active,
	.notification_widget.warning.active,
	.open > .dropdown-toggle.notification_widget.warning {
	background-image: none;
	}
	.notification_widget.warning.disabled:hover,
	.notification_widget.warning[disabled]:hover,
	fieldset[disabled] .notification_widget.warning:hover,
	.notification_widget.warning.disabled:focus,
	.notification_widget.warning[disabled]:focus,
	fieldset[disabled] .notification_widget.warning:focus,
	.notification_widget.warning.disabled.focus,
	.notification_widget.warning[disabled].focus,
	fieldset[disabled] .notification_widget.warning.focus {
	background-color: #f0ad4e;
	border-color: #eea236;
	}
	.notification_widget.warning .badge {
	color: #f0ad4e;
	background-color: #fff;
	}
	.notification_widget.success {
	color: #fff;
	background-color: #5cb85c;
	border-color: #4cae4c;
	}
	.notification_widget.success:focus,
	.notification_widget.success.focus {
	color: #fff;
	background-color: #449d44;
	border-color: #255625;
	}
	.notification_widget.success:hover {
	color: #fff;
	background-color: #449d44;
	border-color: #398439;
	}
	.notification_widget.success:active,
	.notification_widget.success.active,
	.open > .dropdown-toggle.notification_widget.success {
	color: #fff;
	background-color: #449d44;
	border-color: #398439;
	}
	.notification_widget.success:active:hover,
	.notification_widget.success.active:hover,
	.open > .dropdown-toggle.notification_widget.success:hover,
	.notification_widget.success:active:focus,
	.notification_widget.success.active:focus,
	.open > .dropdown-toggle.notification_widget.success:focus,
	.notification_widget.success:active.focus,
	.notification_widget.success.active.focus,
	.open > .dropdown-toggle.notification_widget.success.focus {
	color: #fff;
	background-color: #398439;
	border-color: #255625;
	}
	.notification_widget.success:active,
	.notification_widget.success.active,
	.open > .dropdown-toggle.notification_widget.success {
	background-image: none;
	}
	.notification_widget.success.disabled:hover,
	.notification_widget.success[disabled]:hover,
	fieldset[disabled] .notification_widget.success:hover,
	.notification_widget.success.disabled:focus,
	.notification_widget.success[disabled]:focus,
	fieldset[disabled] .notification_widget.success:focus,
	.notification_widget.success.disabled.focus,
	.notification_widget.success[disabled].focus,
	fieldset[disabled] .notification_widget.success.focus {
	background-color: #5cb85c;
	border-color: #4cae4c;
	}
	.notification_widget.success .badge {
	color: #5cb85c;
	background-color: #fff;
	}
	.notification_widget.info {
	color: #fff;
	background-color: #5bc0de;
	border-color: #46b8da;
	}
	.notification_widget.info:focus,
	.notification_widget.info.focus {
	color: #fff;
	background-color: #31b0d5;
	border-color: #1b6d85;
	}
	.notification_widget.info:hover {
	color: #fff;
	background-color: #31b0d5;
	border-color: #269abc;
	}
	.notification_widget.info:active,
	.notification_widget.info.active,
	.open > .dropdown-toggle.notification_widget.info {
	color: #fff;
	background-color: #31b0d5;
	border-color: #269abc;
	}
	.notification_widget.info:active:hover,
	.notification_widget.info.active:hover,
	.open > .dropdown-toggle.notification_widget.info:hover,
	.notification_widget.info:active:focus,
	.notification_widget.info.active:focus,
	.open > .dropdown-toggle.notification_widget.info:focus,
	.notification_widget.info:active.focus,
	.notification_widget.info.active.focus,
	.open > .dropdown-toggle.notification_widget.info.focus {
	color: #fff;
	background-color: #269abc;
	border-color: #1b6d85;
	}
	.notification_widget.info:active,
	.notification_widget.info.active,
	.open > .dropdown-toggle.notification_widget.info {
	background-image: none;
	}
	.notification_widget.info.disabled:hover,
	.notification_widget.info[disabled]:hover,
	fieldset[disabled] .notification_widget.info:hover,
	.notification_widget.info.disabled:focus,
	.notification_widget.info[disabled]:focus,
	fieldset[disabled] .notification_widget.info:focus,
	.notification_widget.info.disabled.focus,
	.notification_widget.info[disabled].focus,
	fieldset[disabled] .notification_widget.info.focus {
	background-color: #5bc0de;
	border-color: #46b8da;
	}
	.notification_widget.info .badge {
	color: #5bc0de;
	background-color: #fff;
	}
	.notification_widget.danger {
	color: #fff;
	background-color: #d9534f;
	border-color: #d43f3a;
	}
	.notification_widget.danger:focus,
	.notification_widget.danger.focus {
	color: #fff;
	background-color: #c9302c;
	border-color: #761c19;
	}
	.notification_widget.danger:hover {
	color: #fff;
	background-color: #c9302c;
	border-color: #ac2925;
	}
	.notification_widget.danger:active,
	.notification_widget.danger.active,
	.open > .dropdown-toggle.notification_widget.danger {
	color: #fff;
	background-color: #c9302c;
	border-color: #ac2925;
	}
	.notification_widget.danger:active:hover,
	.notification_widget.danger.active:hover,
	.open > .dropdown-toggle.notification_widget.danger:hover,
	.notification_widget.danger:active:focus,
	.notification_widget.danger.active:focus,
	.open > .dropdown-toggle.notification_widget.danger:focus,
	.notification_widget.danger:active.focus,
	.notification_widget.danger.active.focus,
	.open > .dropdown-toggle.notification_widget.danger.focus {
	color: #fff;
	background-color: #ac2925;
	border-color: #761c19;
	}
	.notification_widget.danger:active,
	.notification_widget.danger.active,
	.open > .dropdown-toggle.notification_widget.danger {
	background-image: none;
	}
	.notification_widget.danger.disabled:hover,
	.notification_widget.danger[disabled]:hover,
	fieldset[disabled] .notification_widget.danger:hover,
	.notification_widget.danger.disabled:focus,
	.notification_widget.danger[disabled]:focus,
	fieldset[disabled] .notification_widget.danger:focus,
	.notification_widget.danger.disabled.focus,
	.notification_widget.danger[disabled].focus,
	fieldset[disabled] .notification_widget.danger.focus {
	background-color: #d9534f;
	border-color: #d43f3a;
	}
	.notification_widget.danger .badge {
	color: #d9534f;
	background-color: #fff;
	}
	div#pager {
	background-color: #fff;
	font-size: 14px;
	line-height: 20px;
	overflow: hidden;
	display: none;
	position: fixed;
	bottom: 0px;
	width: 100%;
	max-height: 50%;
	padding-top: 8px;
	-webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
	box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
	/* Display over codemirror */
	z-index: 100;
	/* Hack which prevents jquery ui resizable from changing top. */
	top: auto !important;
	}
	div#pager pre {
	line-height: 1.21429em;
	color: #000;
	background-color: #f7f7f7;
	padding: 0.4em;
	}
	div#pager #pager-button-area {
	position: absolute;
	top: 8px;
	right: 20px;
	}
	div#pager #pager-contents {
	position: relative;
	overflow: auto;
	width: 100%;
	height: 100%;
	}
	div#pager #pager-contents #pager-container {
	position: relative;
	padding: 15px 0px;
	box-sizing: border-box;
	-moz-box-sizing: border-box;
	-webkit-box-sizing: border-box;
	}
	div#pager .ui-resizable-handle {
	top: 0px;
	height: 8px;
	background: #f7f7f7;
	border-top: 1px solid #cfcfcf;
	border-bottom: 1px solid #cfcfcf;
	/* This injects handle bars (a short, wide = symbol) for
	the resize handle. */
	}
	div#pager .ui-resizable-handle::after {
	content: '';
	top: 2px;
	left: 50%;
	height: 3px;
	width: 30px;
	margin-left: -15px;
	position: absolute;
	border-top: 1px solid #cfcfcf;
	}
	.quickhelp {
	/* Old browsers */
	display: -webkit-box;
	-webkit-box-orient: horizontal;
	-webkit-box-align: stretch;
	display: -moz-box;
	-moz-box-orient: horizontal;
	-moz-box-align: stretch;
	display: box;
	box-orient: horizontal;
	box-align: stretch;
	/* Modern browsers */
	display: flex;
	flex-direction: row;
	align-items: stretch;
	line-height: 1.8em;
	}
	.shortcut_key {
	display: inline-block;
	width: 21ex;
	text-align: right;
	font-family: monospace;
	}
	.shortcut_descr {
	display: inline-block;
	/* Old browsers */
	-webkit-box-flex: 1;
	-moz-box-flex: 1;
	box-flex: 1;
	/* Modern browsers */
	flex: 1;
	}
	span.save_widget {
	margin-top: 6px;
	}
	span.save_widget span.filename {
	height: 1em;
	line-height: 1em;
	padding: 3px;
	margin-left: 16px;
	border: none;
	font-size: 146.5%;
	border-radius: 2px;
	}
	span.save_widget span.filename:hover {
	background-color: #e6e6e6;
	}
	span.checkpoint_status,
	span.autosave_status {
	font-size: small;
	}
	@media (max-width: 767px) {
	span.save_widget {
	font-size: small;
	}
	span.checkpoint_status,
	span.autosave_status {
	display: none;
	}
	}
	@media (min-width: 768px) and (max-width: 991px) {
	span.checkpoint_status {
	display: none;
	}
	span.autosave_status {
	font-size: x-small;
	}
	}
	.toolbar {
	padding: 0px;
	margin-left: -5px;
	margin-top: 2px;
	margin-bottom: 5px;
	box-sizing: border-box;
	-moz-box-sizing: border-box;
	-webkit-box-sizing: border-box;
	}
	.toolbar select,
	.toolbar label {
	width: auto;
	vertical-align: middle;
	margin-right: 2px;
	margin-bottom: 0px;
	display: inline;
	font-size: 92%;
	margin-left: 0.3em;
	margin-right: 0.3em;
	padding: 0px;
	padding-top: 3px;
	}
	.toolbar .btn {
	padding: 2px 8px;
	}
	.toolbar .btn-group {
	margin-top: 0px;
	margin-left: 5px;
	}
	#maintoolbar {
	margin-bottom: -3px;
	margin-top: -8px;
	border: 0px;
	min-height: 27px;
	margin-left: 0px;
	padding-top: 11px;
	padding-bottom: 3px;
	}
	#maintoolbar .navbar-text {
	float: none;
	vertical-align: middle;
	text-align: right;
	margin-left: 5px;
	margin-right: 0px;
	margin-top: 0px;
	}
	.select-xs {
	height: 24px;
	}
	.pulse,
	.dropdown-menu > li > a.pulse,
	li.pulse > a.dropdown-toggle,
	li.pulse.open > a.dropdown-toggle {
	background-color: #F37626;
	color: white;
	}
	/**
	* Primary styles
	*
	* Author: Jupyter Development Team
	*/
	/** WARNING IF YOU ARE EDITTING THIS FILE, if this is a .css file, It has a lot
	* of chance of beeing generated from the ../less/[samename].less file, you can
	* try to get back the less file by reverting somme commit in history
	**/
	/*
	* We'll try to get something pretty, so we
	* have some strange css to have the scroll bar on
	* the left with fix button on the top right of the tooltip
	*/
	@-moz-keyframes fadeOut {
	from {
	opacity: 1;
	}
	to {
	opacity: 0;
	}
	}
	@-webkit-keyframes fadeOut {
	from {
	opacity: 1;
	}
	to {
	opacity: 0;
	}
	}
	@-moz-keyframes fadeIn {
	from {
	opacity: 0;
	}
	to {
	opacity: 1;
	}
	}
	@-webkit-keyframes fadeIn {
	from {
	opacity: 0;
	}
	to {
	opacity: 1;
	}
	}
	/properties of tooltip after "expand"/
	.bigtooltip {
	overflow: auto;
	height: 200px;
	-webkit-transition-property: height;
	-webkit-transition-duration: 500ms;
	-moz-transition-property: height;
	-moz-transition-duration: 500ms;
	transition-property: height;
	transition-duration: 500ms;
	}
	/properties of tooltip before "expand"/
	.smalltooltip {
	-webkit-transition-property: height;
	-webkit-transition-duration: 500ms;
	-moz-transition-property: height;
	-moz-transition-duration: 500ms;
	transition-property: height;
	transition-duration: 500ms;
	text-overflow: ellipsis;
	overflow: hidden;
	height: 80px;
	}
	.tooltipbuttons {
	position: absolute;
	padding-right: 15px;
	top: 0px;
	right: 0px;
	}
	.tooltiptext {
	/avoid the button to overlap on some docstring/
	padding-right: 30px;
	}
	.ipython_tooltip {
	max-width: 700px;
	/fade-in animation when inserted/
	-webkit-animation: fadeOut 400ms;
	-moz-animation: fadeOut 400ms;
	animation: fadeOut 400ms;
	-webkit-animation: fadeIn 400ms;
	-moz-animation: fadeIn 400ms;
	animation: fadeIn 400ms;
	vertical-align: middle;
	background-color: #f7f7f7;
	overflow: visible;
	border: #ababab 1px solid;
	outline: none;
	padding: 3px;
	margin: 0px;
	padding-left: 7px;
	font-family: monospace;
	min-height: 50px;
	-moz-box-shadow: 0px 6px 10px -1px #adadad;
	-webkit-box-shadow: 0px 6px 10px -1px #adadad;
	box-shadow: 0px 6px 10px -1px #adadad;
	border-radius: 2px;
	position: absolute;
	z-index: 1000;
	}
	.ipython_tooltip a {
	float: right;
	}
	.ipython_tooltip .tooltiptext pre {
	border: 0;
	border-radius: 0;
	font-size: 100%;
	background-color: #f7f7f7;
	}
	.pretooltiparrow {
	left: 0px;
	margin: 0px;
	top: -16px;
	width: 40px;
	height: 16px;
	overflow: hidden;
	position: absolute;
	}
	.pretooltiparrow:before {
	background-color: #f7f7f7;
	border: 1px #ababab solid;
	z-index: 11;
	content: "";
	position: absolute;
	left: 15px;
	top: 10px;
	width: 25px;
	height: 25px;
	-webkit-transform: rotate(45deg);
	-moz-transform: rotate(45deg);
	-ms-transform: rotate(45deg);
	-o-transform: rotate(45deg);
	}
	ul.typeahead-list i {
	margin-left: -10px;
	width: 18px;
	}
	ul.typeahead-list {
	max-height: 80vh;
	overflow: auto;
	}
	ul.typeahead-list > li > a {
	/ Firefox bug /
	/* see https://github.com/jupyter/notebook/issues/559 */
	white-space: normal;
	}
	.cmd-palette .modal-body {
	padding: 7px;
	}
	.cmd-palette form {
	background: white;
	}
	.cmd-palette input {
	outline: none;
	}
	.no-shortcut {
	display: none;
	}
	.command-shortcut:before {
	content: "(command)";
	padding-right: 3px;
	color: #777777;
	}
	.edit-shortcut:before {
	content: "(edit)";
	padding-right: 3px;
	color: #777777;
	}
	#find-and-replace #replace-preview .match,
	#find-and-replace #replace-preview .insert {
	background-color: #BBDEFB;
	border-color: #90CAF9;
	border-style: solid;
	border-width: 1px;
	border-radius: 0px;
	}
	#find-and-replace #replace-preview .replace .match {
	background-color: #FFCDD2;
	border-color: #EF9A9A;
	border-radius: 0px;
	}
	#find-and-replace #replace-preview .replace .insert {
	background-color: #C8E6C9;
	border-color: #A5D6A7;
	border-radius: 0px;
	}
	#find-and-replace #replace-preview {
	max-height: 60vh;
	overflow: auto;
	}
	#find-and-replace #replace-preview pre {
	padding: 5px 10px;
	}
	.terminal-app {
	background: #EEE;
	}
	.terminal-app #header {
	background: #fff;
	-webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
	box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
	}
	.terminal-app .terminal {
	width: 100%;
	float: left;
	font-family: monospace;
	color: white;
	background: black;
	padding: 0.4em;
	border-radius: 2px;
	-webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.4);
	box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.4);
	}
	.terminal-app .terminal,
	.terminal-app .terminal dummy-screen {
	line-height: 1em;
	font-size: 14px;
	}
	.terminal-app .terminal .xterm-rows {
	padding: 10px;
	}
	.terminal-app .terminal-cursor {
	color: black;
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	<h1 id="AutoML:-Automatic-Machine-Learning">AutoML: Automatic Machine Learning<a class="anchor-link" href="#AutoML:-Automatic-Machine-Learning">¶</a></h1><p>AutoML: Automatic Machine Learning</p>
	<p>H2O’s AutoML is used for automating the machine learning workflow, which includes automatic training and tuning of many models within a user-specified time-limit. Stacked Ensembles will be automatically trained on collections of individual models to produce highly predictive ensemble models which, in most cases, will be the top performing models in the AutoML Leaderboard.</p>

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	<h2 id="Tutorials">Tutorials<a class="anchor-link" href="#Tutorials">¶</a></h2><ul>
	<li>Intro to AutoML + Hands-on Lab - Erin LeDell, Machine Learning Scientist... <a href="https://youtu.be/42Oo8TOl85I">https://youtu.be/42Oo8TOl85I</a> </li>
	<li><p>Scalable Automatic Machine Learning in H2O <a href="https://youtu.be/j6rqrEYQNdo">https://youtu.be/j6rqrEYQNdo</a></p>
	</li>
	<li><p>Scalable Automatic Machine Learning in H2O <a href="https://youtu.be/j6rqrEYQNdo">https://youtu.be/j6rqrEYQNdo</a></p>
	</li>
	</ul>

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	<h2 id="Installing-H2O-and-h2o-python">Installing H2O and h2o python<a class="anchor-link" href="#Installing-H2O-and-h2o-python">¶</a></h2><p>See <a href="http://docs.h2o.ai/h2o/latest-stable/h2o-docs/downloading.html">http://docs.h2o.ai/h2o/latest-stable/h2o-docs/downloading.html</a></p>
	<p>Click the Download H2O button on the <a href="http://h2o-release.s3.amazonaws.com/h2o/latest_stable.html">http://h2o-release.s3.amazonaws.com/h2o/latest_stable.html</a> page. This downloads a zip file that contains everything you need to get started.</p>
	<div class="highlight"><pre><span></span><span class="nb">cd</span> ~/Downloads
	unzip h2o-3.20.0.1.zip
	<span class="nb">cd</span> h2o-3.20.0.1
	java -jar h2o.jar
	</pre></div>
	<p>Point your browser to <a href="http://localhost:54321">http://localhost:54321</a>.</p>
	<p><strong>Install in Python</strong></p>
	<p>Install dependencies (prepending with sudo if needed):</p>
	<div class="highlight"><pre><span></span>pip install requests
	pip install tabulate
	pip install scikit-learn
	pip install colorama
	pip install future
	</pre></div>
	<p>Remove any existing H2O module for Python.</p>
	<div class="highlight"><pre><span></span>pip uninstall h2o
	</pre></div>
	<p>Use pip to install this version of the H2O Python module.</p>
	<div class="highlight"><pre><span></span>pip install -f http://h2o-release.s3.amazonaws.com/h2o/latest_stable_Py.html h2o
	</pre></div>
	<p>Note: When installing H2O from pip in OS X El Capitan, users must include the --user flag. For example:</p>
	<div class="highlight"><pre><span></span>pip install -f http://h2o-release.s3.amazonaws.com/h2o/latest_stable_Py.html h2o --user
	</pre></div>
	<p>Initialize H2O in Python and run a demo to see H2O at work.</p>
	<div class="highlight"><pre><span></span><span class="n">python</span>
	<span class="kn">import</span> <span class="nn">h2o</span>
	<span class="n">h2o</span><span class="o">.</span><span class="n">init</span><span class="p">()</span>
	<span class="n">h2o</span><span class="o">.</span><span class="n">demo</span><span class="p">(</span><span class="s2">"glm"</span><span class="p">)</span>
	</pre></div>

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	<h2 id="Saving-data">Saving data<a class="anchor-link" href="#Saving-data">¶</a></h2><p>H2O model file file will be saved in one of two formats.</p>
	<p>There are two ways to save the leader model -- binary format and MOJO format. If you're taking your leader model to production, then we'd suggest the MOJO format since it's optimized for production use.</p>
	<p>See <a href="http://docs.h2o.ai/h2o/latest-stable/h2o-docs/save-and-load-model.html">http://docs.h2o.ai/h2o/latest-stable/h2o-docs/save-and-load-model.html</a></p>
	<div class="highlight"><pre><span></span><span class="c1"># save the model</span>
	<span class="n">model_path</span> <span class="o">=</span> <span class="n">h2o</span><span class="o">.</span><span class="n">save_model</span><span class="p">(</span><span class="n">model</span><span class="o">=</span><span class="n">model</span><span class="p">,</span> <span class="n">path</span><span class="o">=</span><span class="s2">"/tmp/mymodel"</span><span class="p">,</span> <span class="n">force</span><span class="o">=</span><span class="bp">True</span><span class="p">)</span>

	<span class="c1"># or</span>

	<span class="n">h2o</span><span class="o">.</span><span class="n">save_model</span><span class="p">(</span><span class="n">aml</span><span class="o">.</span><span class="n">leader</span><span class="p">,</span> <span class="n">path</span> <span class="o">=</span> <span class="s2">"./models"</span><span class="p">)</span>

	<span class="c1"># or</span>

	<span class="n">aml</span><span class="o">.</span><span class="n">leader</span><span class="o">.</span><span class="n">download_mojo</span><span class="p">(</span><span class="n">path</span> <span class="o">=</span> <span class="s2">"./models"</span><span class="p">)</span>

	<span class="c1"># load the model</span>
	<span class="n">saved_model</span> <span class="o">=</span> <span class="n">h2o</span><span class="o">.</span><span class="n">load_model</span><span class="p">(</span><span class="n">model_path</span><span class="p">)</span>
	</pre></div>
	<p><strong>Saving data from runs</strong></p>
	<p>Stats about the models can be saved as text or csv or put directly in a database.</p>
	<p>Much of the data is gathered by converting H2O objects to pandas data frame. So anything that a pandas data frame can be saved as is supported.
	<a href="https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.html">https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.html</a></p>
	<div class="highlight"><pre><span></span><span class="n">data_pd</span> <span class="o">=</span> <span class="nb">object</span><span class="o">.</span><span class="n">as_data_frame</span><span class="p">(</span><span class="n">use_pandas</span><span class="o">=</span><span class="bp">True</span><span class="p">)</span>
	</pre></div>
	<p>Otherwise data is returned as python dictionaries or lists.</p>
	<div class="highlight"><pre><span></span><span class="p">[(</span><span class="s1">'addr_state'</span><span class="p">,</span> <span class="mf">258199.28125</span><span class="p">,</span> <span class="mf">1.0</span><span class="p">,</span> <span class="mf">0.19965953057652525</span><span class="p">),</span> <span class="p">(</span><span class="s1">'int_rate'</span><span class="p">,</span> <span class="mf">203347.0625</span><span class="p">,</span> <span class="mf">0.7875585924002257</span><span class="p">,</span> <span class="mf">0.15724357886013807</span><span class="p">),</span> <span class="p">(</span><span class="s1">'dti'</span><span class="p">,</span> <span class="mf">116477.5703125</span><span class="p">,</span> <span class="mf">0.45111500600856147</span><span class="p">,</span> <span class="mf">0.09006941033569575</span><span class="p">),</span> <span class="p">(</span><span class="s1">'revol_util'</span><span class="p">,</span> <span class="mf">110586.1484375</span><span class="p">,</span> <span class="mf">0.42829766179877776</span><span class="p">,</span> <span class="mf">0.08551371010176734</span><span class="p">),</span> <span class="p">(</span><span class="s1">'annual_inc'</span><span class="p">,</span> <span class="mf">96993.90625</span><span class="p">,</span> <span class="mf">0.3756552139898724</span><span class="p">,</span> <span class="mf">0.07500314368384206</span><span class="p">),</span> <span class="p">(</span><span class="s1">'loan_amnt'</span><span class="p">,</span> <span class="mf">95294.5</span><span class="p">,</span> <span class="mf">0.36907345186500207</span><span class="p">,</span> <span class="mf">0.0736890321476241</span><span class="p">),</span> <span class="p">(</span><span class="s1">'total_acc'</span><span class="p">,</span> <span class="mf">90064.8046875</span><span class="p">,</span> <span class="mf">0.3488189597255124</span><span class="p">,</span> <span class="mf">0.06964502975498767</span><span class="p">),</span> <span class="p">(</span><span class="s1">'longest_credit_length'</span><span class="p">,</span> <span class="mf">84291.921875</span><span class="p">,</span> <span class="mf">0.3264607146345416</span><span class="p">,</span> <span class="mf">0.06518099303560954</span><span class="p">),</span> <span class="p">(</span><span class="s1">'purpose'</span><span class="p">,</span> <span class="mf">77462.203125</span><span class="p">,</span> <span class="mf">0.30000936776426446</span><span class="p">,</span> <span class="mf">0.05989972953637317</span><span class="p">),</span> <span class="p">(</span><span class="s1">'emp_length'</span><span class="p">,</span> <span class="mf">63839.28125</span><span class="p">,</span> <span class="mf">0.24724809821677224</span><span class="p">,</span> <span class="mf">0.04936543922589935</span><span class="p">),</span> <span class="p">(</span><span class="s1">'term'</span><span class="p">,</span> <span class="mf">34895.7265625</span><span class="p">,</span> <span class="mf">0.1351503629040408</span><span class="p">,</span> <span class="mf">0.02698405801466782</span><span class="p">),</span> <span class="p">(</span><span class="s1">'home_ownership'</span><span class="p">,</span> <span class="mf">26499.876953125</span><span class="p">,</span> <span class="mf">0.10263342649457897</span><span class="p">,</span> <span class="mf">0.02049174175536795</span><span class="p">),</span> <span class="p">(</span><span class="s1">'delinq_2yrs'</span><span class="p">,</span> <span class="mf">20556.2578125</span><span class="p">,</span> <span class="mf">0.0796139234508423</span><span class="p">,</span> <span class="mf">0.015895678583550586</span><span class="p">),</span> <span class="p">(</span><span class="s1">'verification_status'</span><span class="p">,</span> <span class="mf">14689.3369140625</span><span class="p">,</span> <span class="mf">0.056891470971368166</span><span class="p">,</span> <span class="mf">0.01135892438795138</span><span class="p">)]</span>
	</pre></div>

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	<h2 id="Starting-H2O-server">Starting H2O server<a class="anchor-link" href="#Starting-H2O-server">¶</a></h2>
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	<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># import h2o package and specific estimator </span>
	<span class="kn">import</span> <span class="nn">h2o</span>
	<span class="kn">from</span> <span class="nn">h2o.automl</span> <span class="k">import</span> <span class="n">H2OAutoML</span>
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	<p>h2o.init with python seems very sensitive the the H2O version. If the H2O cluster version is 3.20.0.1 and the python h2o library is 3.19.0 it will fail so we set strict_version_check=False</p>
	<p>If the H2O cluster isn't found h2o.init will start one.</p>
	<p>Note that the current script starts each H2O instance on a different port. It's not clear why but should we do this we should choose from only the higher ports.</p>
	<p>A port number is a 16-bit unsigned integer, thus ranging from 0 to 65535. There is no reason to choose a port less than 10000.</p>

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	<div class=" highlight hl-ipython3"><pre><span></span><span class="n">h2o</span><span class="o">.</span><span class="n">init</span><span class="p">(</span><span class="n">strict_version_check</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span> <span class="c1"># start h2o</span>
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	<pre>Checking whether there is an H2O instance running at http://localhost:54321. connected.
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	<div style="overflow:auto"><table style="width:50%"><tr><td>H2O cluster uptime:</td>
	<td>10 mins 06 secs</td></tr>
	<tr><td>H2O cluster timezone:</td>
	<td>America/New_York</td></tr>
	<tr><td>H2O data parsing timezone:</td>
	<td>UTC</td></tr>
	<tr><td>H2O cluster version:</td>
	<td>3.20.0.1</td></tr>
	<tr><td>H2O cluster version age:</td>
	<td>5 months and 13 days !!!</td></tr>
	<tr><td>H2O cluster name:</td>
	<td>H2O_from_python_bear_07058y</td></tr>
	<tr><td>H2O cluster total nodes:</td>
	<td>1</td></tr>
	<tr><td>H2O cluster free memory:</td>
	<td>2.129 Gb</td></tr>
	<tr><td>H2O cluster total cores:</td>
	<td>8</td></tr>
	<tr><td>H2O cluster allowed cores:</td>
	<td>8</td></tr>
	<tr><td>H2O cluster status:</td>
	<td>locked, healthy</td></tr>
	<tr><td>H2O connection url:</td>
	<td>http://localhost:54321</td></tr>
	<tr><td>H2O connection proxy:</td>
	<td>None</td></tr>
	<tr><td>H2O internal security:</td>
	<td>False</td></tr>
	<tr><td>H2O API Extensions:</td>
	<td>XGBoost, Algos, AutoML, Core V3, Core V4</td></tr>
	<tr><td>Python version:</td>
	<td>3.6.5 final</td></tr></table></div>
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	<h2 id="h2o.automl-Parameters">h2o.automl Parameters<a class="anchor-link" href="#h2o.automl-Parameters">¶</a></h2><p><a href="http://docs.h2o.ai/h2o/latest-stable/h2o-docs/automl.html">http://docs.h2o.ai/h2o/latest-stable/h2o-docs/automl.html</a></p>
	<p>NB: Eventually one wants to expose all the parameters to the expert user.</p>
	<p><strong>Required Data Parameters</strong></p>
	<p>y: This argument is the name (or index) of the response column.</p>
	<p>training_frame: Specifies the training set.</p>
	<p>The user gives the name of the depenent variable and training file name.</p>
	<p><strong>Required Stopping Parameters</strong></p>
	<p>One of the following stopping strategies (time or number-of-model based) must be specified. When both options are set, then the AutoML run will stop as soon as it hits one of either of these limits.</p>
	<p>max_runtime_secs: This argument controls how long the AutoML run will execute for. This defaults to 3600 seconds (1 hour).</p>
	<p>max_models: Specify the maximum number of models to build in an AutoML run, excluding the Stacked Ensemble models. Defaults to NULL/None.</p>
	<h3 id="Optional-Parameters">Optional Parameters<a class="anchor-link" href="#Optional-Parameters">¶</a></h3><p><strong>Optional Data Parameters</strong></p>
	<p>x: A list/vector of predictor column names or indexes. This argument only needs to be specified if the user wants to exclude columns from the set of predictors. If all columns (other than the response) should be used in prediction, then this does not need to be set.</p>
	<p>validation_frame: This argument is used to specify the validation frame used for early stopping of individual models and early stopping of the grid searches (unless max_models or max_runtime_secs overrides metric-based early stopping).</p>
	<p>leaderboard_frame: This argument allows the user to specify a particular data frame use to score & rank models on the leaderboard. This frame will not be used for anything besides leaderboard scoring. If a leaderboard frame is not specified by the user, then the leaderboard will use cross-validation metrics instead (or if cross-validation is turned off by setting nfolds = 0, then a leaderboard frame will be generated automatically from the validation frame (if provided) or the training frame).</p>
	<p>fold_column: Specifies a column with cross-validation fold index assignment per observation. This is used to override the default, randomized, 5-fold cross-validation scheme for individual models in the AutoML run.</p>
	<p>weights_column: Specifies a column with observation weights. Giving some observation a weight of zero is equivalent to excluding it from the dataset; giving an observation a relative weight of 2 is equivalent to repeating that row twice. Negative weights are not allowed.</p>
	<p>ignored_columns: (Optional, Python only) Specify the column or columns (as a list/vector) to be excluded from the model. This is the converse of the x argument.</p>
	<p><strong>Optional Miscellaneous Parameters</strong></p>
	<p>nfolds: Number of folds for k-fold cross-validation of the models in the AutoML run. Defaults to 5. Use 0 to disable cross-validation; this will also disable Stacked Ensembles (thus decreasing the overall best model performance).</p>
	<p>balance_classes: Specify whether to oversample the minority classes to balance the class distribution. This option is not enabled by default and can increase the data frame size. This option is only applicable for classification. Majority classes can be undersampled to satisfy the max_after_balance_size parameter.</p>
	<p>class_sampling_factors: Specify the per-class (in lexicographical order) over/under-sampling ratios. By default, these ratios are automatically computed during training to obtain the class balance.</p>
	<p>max_after_balance_size: Specify the maximum relative size of the training data after balancing class counts (balance_classes must be enabled). Defaults to 5.0. (The value can be less than 1.0).</p>
	<p>stopping_metric: Specifies the metric to use for early stopping of the grid searches and individual models. Defaults to "AUTO". The available options are:</p>
	<p>AUTO: This defaults to logloss for classification, deviance for regression
	deviance (mean residual deviance)
	logloss
	MSE
	RMSE
	MAE
	RMSLE
	AUC
	lift_top_group
	misclassification
	mean_per_class_error</p>
	<p>stopping_tolerance: This option specifies the relative tolerance for the metric-based stopping criterion to stop a grid search and the training of individual models within the AutoML run. This value defaults to 0.001 if the dataset is at least 1 million rows; otherwise it defaults to a bigger value determined by the size of the dataset and the non-NA-rate. In that case, the value is computed as 1/sqrt(nrows * non-NA-rate).</p>
	<p>stopping_rounds: This argument is used to stop model training when the stopping metric (e.g. AUC) doesn’t improve for this specified number of training rounds, based on a simple moving average. In the context of AutoML, this controls early stopping both within the random grid searches as well as the individual models. Defaults to 3 and must be an non-negative integer. To disable early stopping altogether, set this to 0.</p>
	<p>sort_metric: Specifies the metric used to sort the Leaderboard by at the end of an AutoML run. Available options include:</p>
	<p>AUTO: This defaults to AUC for binary classification, mean_per_class_error for multinomial classification, and deviance for regression.
	deviance (mean residual deviance)
	logloss
	MSE
	RMSE
	MAE
	RMSLE
	AUC
	mean_per_class_error</p>
	<p>seed: Integer. Set a seed for reproducibility. AutoML can only guarantee reproducibility if max_models is used because max_runtime_secs is resource limited, meaning that if the available compute resources are not the same between runs, AutoML may be able to train more models on one run vs another. Defaults to NULL/None.</p>
	<p>project_name: Character string to identify an AutoML project. Defaults to NULL/None, which means a project name will be auto-generated based on the training frame ID. More models can be trained and added to an existing AutoML project by specifying the same project name in muliple calls to the AutoML function (as long as the same training frame is used in subsequent runs).</p>
	<p>exclude_algos: List/vector of character strings naming the algorithms to skip during the model-building phase. An example use is exclude_algos = ["GLM", "DeepLearning", "DRF"] in Python or exclude_algos = c("GLM", "DeepLearning", "DRF") in R. Defaults to None/NULL, which means that all appropriate H2O algorithms will be used, if the search stopping criteria allow. The algorithm names are:</p>
	<p>GLM
	DeepLearning
	GBM
	DRF (This includes both the Random Forest and Extremely Randomized Trees (XRT) models. Refer to the Extremely Randomized Trees section in the DRF chapter and the histogram_type parameter description for more information.)
	StackedEnsemble
	keep_cross_validation_predictions: Specify whether to keep the predictions of the cross-validation predictions. If set to FALSE, then running the same AutoML object for repeated runs will cause an exception because CV predictions are are required to build additional Stacked Ensemble models in AutoML. This option defaults to TRUE.</p>
	<p>keep_cross_validation_models: Specify whether to keep the cross-validated models. Deleting cross-validation models will save memory in the H2O cluster. This option defaults to TRUE.</p>

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	<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Assume the following are passed by the user from the web interface</span>

	<span class="sd">'''</span>
	<span class="sd">Need a user id and project id?</span>

	<span class="sd">'''</span>
	<span class="n">target</span><span class="o">=</span><span class="s1">'bad_loan'</span>
	<span class="n">data_file</span><span class="o">=</span><span class="s1">'loan.csv'</span>
	<span class="n">run_time</span><span class="o">=</span><span class="mi">333</span>
	<span class="n">run_id</span><span class="o">=</span><span class="s1">'SOME_ID_20180617_221529'</span> <span class="c1"># Just some arbitrary ID</span>
	<span class="n">server_path</span><span class="o">=</span><span class="s1">'/Users/bear/Documents/INFO_7390/H2O'</span>
	<span class="n">classification</span><span class="o">=</span><span class="kc">True</span>
	<span class="n">scale</span><span class="o">=</span><span class="kc">False</span>
	<span class="n">max_models</span><span class="o">=</span><span class="kc">None</span>
	<span class="n">balance_y</span><span class="o">=</span><span class="kc">False</span> <span class="c1"># balance_classes=balance_y</span>
	<span class="n">balance_threshold</span><span class="o">=</span><span class="mf">0.2</span>
	<span class="n">project</span> <span class="o">=</span><span class="s2">"automl_test"</span> <span class="c1"># project_name = project</span>
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	<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Use local data file or download from some type of bucket</span>
	<span class="kn">import</span> <span class="nn">os</span>

	<span class="n">data_path</span><span class="o">=</span><span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">server_path</span><span class="p">,</span><span class="n">data_file</span><span class="p">)</span>
	<span class="n">data_path</span>
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	<pre>'/Users/bear/Documents/INFO_7390/H2O/loan.csv'</pre>
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	<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Use local data file or download from some type of bucket</span>
	<span class="k">if</span> <span class="ow">not</span> <span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">isfile</span><span class="p">(</span><span class="n">data_path</span><span class="p">):</span>
	<span class="n">data_path</span> <span class="o">=</span> <span class="s1">'https://raw.githubusercontent.com/h2oai/app-consumer-loan/master/data/loan.csv'</span>

	<span class="c1"># Load data into H2O</span>
	<span class="n">df</span> <span class="o">=</span> <span class="n">h2o</span><span class="o">.</span><span class="n">import_file</span><span class="p">(</span><span class="n">data_path</span><span class="p">)</span>
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	<pre>Parse progress: \|█████████████████████████████████████████████████████████\| 100%
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	<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df</span><span class="o">.</span><span class="n">describe</span><span class="p">()</span>
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	<pre>Rows:163987
	Cols:15


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	<table>
	<thead>
	<tr><th> </th><th>loan_amnt </th><th>term </th><th>int_rate </th><th>emp_length </th><th>home_ownership </th><th>annual_inc </th><th>purpose </th><th>addr_state </th><th>dti </th><th>delinq_2yrs </th><th>revol_util </th><th>total_acc </th><th>bad_loan </th><th>longest_credit_length </th><th>verification_status </th></tr>
	</thead>
	<tbody>
	<tr><td>type </td><td>int </td><td>enum </td><td>real </td><td>int </td><td>enum </td><td>real </td><td>enum </td><td>enum </td><td>real </td><td>int </td><td>real </td><td>int </td><td>int </td><td>int </td><td>enum </td></tr>
	<tr><td>mins </td><td>500.0 </td><td> </td><td>5.42 </td><td>0.0 </td><td> </td><td>1896.0 </td><td> </td><td> </td><td>0.0 </td><td>0.0 </td><td>0.0 </td><td>1.0 </td><td>0.0 </td><td>0.0 </td><td> </td></tr>
	<tr><td>mean </td><td>13074.169141456332</td><td> </td><td>13.715904065566189</td><td>5.684352932995338</td><td> </td><td>71915.67051974905</td><td> </td><td> </td><td>15.881530121290167</td><td>0.22735700606252723</td><td>54.07917280242262 </td><td>24.579733834274574</td><td>0.1830388994249544</td><td>14.854273655448333 </td><td> </td></tr>
	<tr><td>maxs </td><td>35000.0 </td><td> </td><td>26.06 </td><td>10.0 </td><td> </td><td>7141778.0 </td><td> </td><td> </td><td>39.99 </td><td>29.0 </td><td>150.70000000000002</td><td>118.0 </td><td>1.0 </td><td>65.0 </td><td> </td></tr>
	<tr><td>sigma </td><td>7993.556188734672 </td><td> </td><td>4.391939870545808 </td><td>3.610663731100238</td><td> </td><td>59070.91565491818</td><td> </td><td> </td><td>7.5876682241925355</td><td>0.6941679229284191 </td><td>25.285366766770498</td><td>11.685190365910666</td><td>0.3866995896078875</td><td>6.947732922546689 </td><td> </td></tr>
	<tr><td>zeros </td><td>0 </td><td> </td><td>0 </td><td>14248 </td><td> </td><td>0 </td><td> </td><td> </td><td>270 </td><td>139459 </td><td>1562 </td><td>0 </td><td>133971 </td><td>11 </td><td> </td></tr>
	<tr><td>missing</td><td>0 </td><td>0 </td><td>0 </td><td>5804 </td><td>0 </td><td>4 </td><td>0 </td><td>0 </td><td>0 </td><td>29 </td><td>193 </td><td>29 </td><td>0 </td><td>29 </td><td>0 </td></tr>
	<tr><td>0 </td><td>5000.0 </td><td>36 months</td><td>10.65 </td><td>10.0 </td><td>RENT </td><td>24000.0 </td><td>credit_card </td><td>AZ </td><td>27.65 </td><td>0.0 </td><td>83.7 </td><td>9.0 </td><td>0.0 </td><td>26.0 </td><td>verified </td></tr>
	<tr><td>1 </td><td>2500.0 </td><td>60 months</td><td>15.27 </td><td>0.0 </td><td>RENT </td><td>30000.0 </td><td>car </td><td>GA </td><td>1.0 </td><td>0.0 </td><td>9.4 </td><td>4.0 </td><td>1.0 </td><td>12.0 </td><td>verified </td></tr>
	<tr><td>2 </td><td>2400.0 </td><td>36 months</td><td>15.96 </td><td>10.0 </td><td>RENT </td><td>12252.0 </td><td>small_business </td><td>IL </td><td>8.72 </td><td>0.0 </td><td>98.5 </td><td>10.0 </td><td>0.0 </td><td>10.0 </td><td>not verified </td></tr>
	<tr><td>3 </td><td>10000.0 </td><td>36 months</td><td>13.49 </td><td>10.0 </td><td>RENT </td><td>49200.0 </td><td>other </td><td>CA </td><td>20.0 </td><td>0.0 </td><td>21.0 </td><td>37.0 </td><td>0.0 </td><td>15.0 </td><td>verified </td></tr>
	<tr><td>4 </td><td>5000.0 </td><td>36 months</td><td>7.9 </td><td>3.0 </td><td>RENT </td><td>36000.0 </td><td>wedding </td><td>AZ </td><td>11.2 </td><td>0.0 </td><td>28.3 </td><td>12.0 </td><td>0.0 </td><td>7.0 </td><td>verified </td></tr>
	<tr><td>5 </td><td>3000.0 </td><td>36 months</td><td>18.64 </td><td>9.0 </td><td>RENT </td><td>48000.0 </td><td>car </td><td>CA </td><td>5.3500000000000005</td><td>0.0 </td><td>87.5 </td><td>4.0 </td><td>0.0 </td><td>4.0 </td><td>verified </td></tr>
	<tr><td>6 </td><td>5600.0 </td><td>60 months</td><td>21.28 </td><td>4.0 </td><td>OWN </td><td>40000.0 </td><td>small_business </td><td>CA </td><td>5.55 </td><td>0.0 </td><td>32.6 </td><td>13.0 </td><td>1.0 </td><td>7.0 </td><td>verified </td></tr>
	<tr><td>7 </td><td>5375.0 </td><td>60 months</td><td>12.69 </td><td>0.0 </td><td>RENT </td><td>15000.0 </td><td>other </td><td>TX </td><td>18.08 </td><td>0.0 </td><td>36.5 </td><td>3.0 </td><td>1.0 </td><td>7.0 </td><td>verified </td></tr>
	<tr><td>8 </td><td>6500.0 </td><td>60 months</td><td>14.65 </td><td>5.0 </td><td>OWN </td><td>72000.0 </td><td>debt_consolidation</td><td>AZ </td><td>16.12 </td><td>0.0 </td><td>20.6 </td><td>23.0 </td><td>0.0 </td><td>13.0 </td><td>not verified </td></tr>
	<tr><td>9 </td><td>12000.0 </td><td>36 months</td><td>12.69 </td><td>10.0 </td><td>OWN </td><td>75000.0 </td><td>debt_consolidation</td><td>CA </td><td>10.78 </td><td>0.0 </td><td>67.10000000000001 </td><td>34.0 </td><td>0.0 </td><td>22.0 </td><td>verified </td></tr>
	</tbody>
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	<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># assign target and inputs for logistic regression</span>
	<span class="n">y</span> <span class="o">=</span> <span class="n">target</span>
	<span class="n">X</span> <span class="o">=</span> <span class="p">[</span><span class="n">name</span> <span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">df</span><span class="o">.</span><span class="n">columns</span> <span class="k">if</span> <span class="n">name</span> <span class="o">!=</span> <span class="n">y</span><span class="p">]</span>
	<span class="nb">print</span><span class="p">(</span><span class="n">y</span><span class="p">)</span>
	<span class="nb">print</span><span class="p">(</span><span class="n">X</span><span class="p">)</span>
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	<pre>bad_loan
	['loan_amnt', 'term', 'int_rate', 'emp_length', 'home_ownership', 'annual_inc', 'purpose', 'addr_state', 'dti', 'delinq_2yrs', 'revol_util', 'total_acc', 'longest_credit_length', 'verification_status']
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	<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># determine column types</span>
	<span class="n">ints</span><span class="p">,</span> <span class="n">reals</span><span class="p">,</span> <span class="n">enums</span> <span class="o">=</span> <span class="p">[],</span> <span class="p">[],</span> <span class="p">[]</span>
	<span class="k">for</span> <span class="n">key</span><span class="p">,</span> <span class="n">val</span> <span class="ow">in</span> <span class="n">df</span><span class="o">.</span><span class="n">types</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
	<span class="k">if</span> <span class="n">key</span> <span class="ow">in</span> <span class="n">X</span><span class="p">:</span>
	<span class="k">if</span> <span class="n">val</span> <span class="o">==</span> <span class="s1">'enum'</span><span class="p">:</span>
	<span class="n">enums</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">key</span><span class="p">)</span>
	<span class="k">elif</span> <span class="n">val</span> <span class="o">==</span> <span class="s1">'int'</span><span class="p">:</span>
	<span class="n">ints</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">key</span><span class="p">)</span>
	<span class="k">else</span><span class="p">:</span>
	<span class="n">reals</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">key</span><span class="p">)</span>

	<span class="nb">print</span><span class="p">(</span><span class="n">ints</span><span class="p">)</span>
	<span class="nb">print</span><span class="p">(</span><span class="n">enums</span><span class="p">)</span>
	<span class="nb">print</span><span class="p">(</span><span class="n">reals</span><span class="p">)</span>
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	<pre>['loan_amnt', 'emp_length', 'delinq_2yrs', 'total_acc', 'longest_credit_length']
	['term', 'home_ownership', 'purpose', 'addr_state', 'verification_status']
	['int_rate', 'annual_inc', 'dti', 'revol_util']
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	<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># impute missing values</span>
	<span class="n">_</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="n">reals</span><span class="p">]</span><span class="o">.</span><span class="n">impute</span><span class="p">(</span><span class="n">method</span><span class="o">=</span><span class="s1">'mean'</span><span class="p">)</span>
	<span class="n">_</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="n">ints</span><span class="p">]</span><span class="o">.</span><span class="n">impute</span><span class="p">(</span><span class="n">method</span><span class="o">=</span><span class="s1">'median'</span><span class="p">)</span>

	<span class="k">if</span> <span class="n">scale</span><span class="p">:</span>
	<span class="n">df</span><span class="p">[</span><span class="n">reals</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="n">reals</span><span class="p">]</span><span class="o">.</span><span class="n">scale</span><span class="p">()</span>
	<span class="n">df</span><span class="p">[</span><span class="n">ints</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="n">ints</span><span class="p">]</span><span class="o">.</span><span class="n">scale</span><span class="p">()</span>
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	<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># set target to factor for classification by default or if user specifies classification</span>
	<span class="k">if</span> <span class="n">classification</span><span class="p">:</span>
	<span class="n">df</span><span class="p">[</span><span class="n">y</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="n">y</span><span class="p">]</span><span class="o">.</span><span class="n">asfactor</span><span class="p">()</span>
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	<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df</span><span class="p">[</span><span class="n">y</span><span class="p">]</span><span class="o">.</span><span class="n">levels</span><span class="p">()</span>
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	<pre>[['0', '1']]</pre>
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	<h3 id="balance_classes-check">balance_classes check<a class="anchor-link" href="#balance_classes-check">¶</a></h3><p>If one class in two class classification is less than 20% of the total then one should set balance_classes=True</p>
	<p>That is,</p>
	<p>balance_classes=balance_y</p>

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	<div class=" highlight hl-ipython3"><pre><span></span><span class="k">if</span> <span class="n">classification</span><span class="p">:</span>
	<span class="n">class_percentage</span> <span class="o">=</span> <span class="n">y_balance</span><span class="o">=</span><span class="n">df</span><span class="p">[</span><span class="n">y</span><span class="p">]</span><span class="o">.</span><span class="n">mean</span><span class="p">()[</span><span class="mi">0</span><span class="p">]</span><span class="o">/</span><span class="p">(</span><span class="n">df</span><span class="p">[</span><span class="n">y</span><span class="p">]</span><span class="o">.</span><span class="n">max</span><span class="p">()</span><span class="o">-</span><span class="n">df</span><span class="p">[</span><span class="n">y</span><span class="p">]</span><span class="o">.</span><span class="n">min</span><span class="p">())</span>
	<span class="k">if</span> <span class="n">class_percentage</span> <span class="o"><</span> <span class="n">balance_threshold</span><span class="p">:</span>
	<span class="n">balance_y</span><span class="o">=</span><span class="kc">True</span>


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	<div class=" highlight hl-ipython3"><pre><span></span><span class="nb">print</span><span class="p">(</span><span class="n">run_time</span><span class="p">)</span>
	<span class="nb">type</span><span class="p">(</span><span class="n">run_time</span><span class="p">)</span>
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	<pre>333
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	<pre>int</pre>
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	<h2 id="Cross-validate-rather-than-take-a-test-training-split">Cross-validate rather than take a test training split<a class="anchor-link" href="#Cross-validate-rather-than-take-a-test-training-split">¶</a></h2><p>Cross-validation rather than taking a test training split reduces the variance of the estimates of goodness of fit statistics. In rare cases one should take a test training split but this should be left to the expert users.</p>
	<p>This also means the pro user can just upload the data and not worry about taking a test training split.</p>
	<p>We can pass the original, full dataset, <code>df</code> (without passing a <code>leaderboard_frame</code>). This is a more efficient use of our data since we can use 100% of the data for training, rather than 80% or so. This time our leaderboard will use cross-validated metrics. It also gives better estimates of goodness of fit statistics.</p>
	<p><em>Note: Using an explicit <code>leaderboard_frame</code> for scoring may be useful in some cases, which is why the option is available.</em></p>
	<p>But it's not preferable in most cases. Leave it as an expert option.</p>

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	<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># automl</span>
	<span class="c1"># runs for run_time seconds then builds a stacked ensemble</span>
	<span class="n">aml</span> <span class="o">=</span> <span class="n">H2OAutoML</span><span class="p">(</span><span class="n">max_runtime_secs</span><span class="o">=</span><span class="n">run_time</span><span class="p">,</span><span class="n">project_name</span> <span class="o">=</span> <span class="n">project</span><span class="p">,</span><span class="n">balance_classes</span><span class="o">=</span><span class="n">balance_y</span><span class="p">)</span> <span class="c1"># init automl, run for 300 seconds</span>
	<span class="n">aml</span><span class="o">.</span><span class="n">train</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="n">X</span><span class="p">,</span>
	<span class="n">y</span><span class="o">=</span><span class="n">y</span><span class="p">,</span>
	<span class="n">training_frame</span><span class="o">=</span><span class="n">df</span><span class="p">)</span>
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	<pre>AutoML progress: \|████████████████████████████████████████████████████████\| 100%
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	<h2 id="Leaderboard">Leaderboard<a class="anchor-link" href="#Leaderboard">¶</a></h2><p>Next, we will view the AutoML Leaderboard. Since we did not specify a <code>leaderboard_frame</code> in the <code>H2OAutoML.train()</code> method for scoring and ranking the models, the AutoML leaderboard uses cross-validation metrics to rank the models.</p>
	<p>A default performance metric for each machine learning task (binary classification, multiclass classification, regression) is specified internally and the leaderboard will be sorted by that metric. In the case of binary classification, the default ranking metric is Area Under the ROC Curve (AUC). In the future, the user will be able to specify any of the H2O metrics so that different metrics can be used to generate rankings on the leaderboard.</p>
	<p>The leader model is stored at <code>aml.leader</code> and the leaderboard is stored at <code>aml.leaderboard</code>.</p>

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	<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># view leaderboard</span>
	<span class="n">lb</span> <span class="o">=</span> <span class="n">aml</span><span class="o">.</span><span class="n">leaderboard</span>
	<span class="n">lb</span>
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	<tr><th>model_id </th><th style="text-align: right;"> auc</th><th style="text-align: right;"> logloss</th><th style="text-align: right;"> mean_per_class_error</th><th style="text-align: right;"> rmse</th><th style="text-align: right;"> mse</th></tr>
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	<tr><td>StackedEnsemble_AllModels_0_AutoML_20181120_154205 </td><td style="text-align: right;">0.70712 </td><td style="text-align: right;"> 0.435531</td><td style="text-align: right;"> 0.349509</td><td style="text-align: right;">0.370103</td><td style="text-align: right;">0.136977</td></tr>
	<tr><td>StackedEnsemble_AllModels_0_AutoML_20181120_153506 </td><td style="text-align: right;">0.706222</td><td style="text-align: right;"> 0.435883</td><td style="text-align: right;"> 0.351685</td><td style="text-align: right;">0.370262</td><td style="text-align: right;">0.137094</td></tr>
	<tr><td>StackedEnsemble_BestOfFamily_0_AutoML_20181120_153506</td><td style="text-align: right;">0.705212</td><td style="text-align: right;"> 0.43622 </td><td style="text-align: right;"> 0.350829</td><td style="text-align: right;">0.370407</td><td style="text-align: right;">0.137202</td></tr>
	<tr><td>GBM_grid_0_AutoML_20181120_154205_model_0 </td><td style="text-align: right;">0.703839</td><td style="text-align: right;"> 0.435055</td><td style="text-align: right;"> 0.353507</td><td style="text-align: right;">0.370225</td><td style="text-align: right;">0.137067</td></tr>
	<tr><td>GBM_grid_0_AutoML_20181120_153506_model_0 </td><td style="text-align: right;">0.703216</td><td style="text-align: right;"> 0.435227</td><td style="text-align: right;"> 0.352786</td><td style="text-align: right;">0.370273</td><td style="text-align: right;">0.137102</td></tr>
	<tr><td>GBM_grid_0_AutoML_20181120_153506_model_1 </td><td style="text-align: right;">0.702313</td><td style="text-align: right;"> 0.435862</td><td style="text-align: right;"> 0.353887</td><td style="text-align: right;">0.370509</td><td style="text-align: right;">0.137277</td></tr>
	<tr><td>GBM_grid_0_AutoML_20181120_154205_model_1 </td><td style="text-align: right;">0.702177</td><td style="text-align: right;"> 0.435943</td><td style="text-align: right;"> 0.354178</td><td style="text-align: right;">0.370554</td><td style="text-align: right;">0.13731 </td></tr>
	<tr><td>GBM_grid_0_AutoML_20181120_153506_model_2 </td><td style="text-align: right;">0.70028 </td><td style="text-align: right;"> 0.437029</td><td style="text-align: right;"> 0.354784</td><td style="text-align: right;">0.370872</td><td style="text-align: right;">0.137546</td></tr>
	<tr><td>GBM_grid_0_AutoML_20181120_154205_model_2 </td><td style="text-align: right;">0.699971</td><td style="text-align: right;"> 0.43737 </td><td style="text-align: right;"> 0.354552</td><td style="text-align: right;">0.371075</td><td style="text-align: right;">0.137696</td></tr>
	<tr><td>DeepLearning_0_AutoML_20181120_154205 </td><td style="text-align: right;">0.699148</td><td style="text-align: right;"> 0.43985 </td><td style="text-align: right;"> 0.355085</td><td style="text-align: right;">0.372547</td><td style="text-align: right;">0.138791</td></tr>
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	<p>Now we will view a snapshot of the top models. Here we should see the two Stacked Ensembles at or near the top of the leaderboard. Stacked Ensembles can almost always outperform a single model.</p>

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	<div class=" highlight hl-ipython3"><pre><span></span><span class="n">aml</span><span class="o">.</span><span class="n">leader</span>
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	<pre>Model Details
	=============
	H2OStackedEnsembleEstimator : Stacked Ensemble
	Model Key: StackedEnsemble_AllModels_0_AutoML_20181120_154205
	No model summary for this model


	ModelMetricsBinomialGLM: stackedensemble
	Reported on train data.

	MSE: 0.12685990330985406
	RMSE: 0.3561739789904002
	LogLoss: 0.40703958453227496
	Null degrees of freedom: 130954
	Residual degrees of freedom: 130943
	Null deviance: 124374.13927893189
	Residual deviance: 106607.73758484815
	AIC: 106631.73758484815
	AUC: 0.7734040182726795
	Gini: 0.5468080365453589
	Confusion Matrix (Act/Pred) for max f1 @ threshold = 0.21708051286464972:
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	<td><b>0</b></td>
	<td><b>1</b></td>
	<td><b>Error</b></td>
	<td><b>Rate</b></td></tr>
	<tr><td>0</td>
	<td>83212.0</td>
	<td>23869.0</td>
	<td>0.2229</td>
	<td> (23869.0/107081.0)</td></tr>
	<tr><td>1</td>
	<td>9376.0</td>
	<td>14498.0</td>
	<td>0.3927</td>
	<td> (9376.0/23874.0)</td></tr>
	<tr><td>Total</td>
	<td>92588.0</td>
	<td>38367.0</td>
	<td>0.2539</td>
	<td> (33245.0/130955.0)</td></tr></table></div>
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	<pre>Maximum Metrics: Maximum metrics at their respective thresholds

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	<div style="overflow:auto"><table style="width:50%"><tr><td><b>metric</b></td>
	<td><b>threshold</b></td>
	<td><b>value</b></td>
	<td><b>idx</b></td></tr>
	<tr><td>max f1</td>
	<td>0.2170805</td>
	<td>0.4658666</td>
	<td>238.0</td></tr>
	<tr><td>max f2</td>
	<td>0.1410190</td>
	<td>0.6067433</td>
	<td>309.0</td></tr>
	<tr><td>max f0point5</td>
	<td>0.3338429</td>
	<td>0.4568693</td>
	<td>155.0</td></tr>
	<tr><td>max accuracy</td>
	<td>0.4390853</td>
	<td>0.8290100</td>
	<td>98.0</td></tr>
	<tr><td>max precision</td>
	<td>0.8006766</td>
	<td>1.0</td>
	<td>0.0</td></tr>
	<tr><td>max recall</td>
	<td>0.0676438</td>
	<td>1.0</td>
	<td>394.0</td></tr>
	<tr><td>max specificity</td>
	<td>0.8006766</td>
	<td>1.0</td>
	<td>0.0</td></tr>
	<tr><td>max absolute_mcc</td>
	<td>0.2335835</td>
	<td>0.3269004</td>
	<td>224.0</td></tr>
	<tr><td>max min_per_class_accuracy</td>
	<td>0.1855661</td>
	<td>0.6993958</td>
	<td>265.0</td></tr>
	<tr><td>max mean_per_class_accuracy</td>
	<td>0.1761337</td>
	<td>0.7006208</td>
	<td>274.0</td></tr></table></div>
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	<pre>Gains/Lift Table: Avg response rate: 18.23 %

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	<td><b>group</b></td>
	<td><b>cumulative_data_fraction</b></td>
	<td><b>lower_threshold</b></td>
	<td><b>lift</b></td>
	<td><b>cumulative_lift</b></td>
	<td><b>response_rate</b></td>
	<td><b>cumulative_response_rate</b></td>
	<td><b>capture_rate</b></td>
	<td><b>cumulative_capture_rate</b></td>
	<td><b>gain</b></td>
	<td><b>cumulative_gain</b></td></tr>
	<tr><td></td>
	<td>1</td>
	<td>0.0100034</td>
	<td>0.5809896</td>
	<td>4.2290904</td>
	<td>4.2290904</td>
	<td>0.7709924</td>
	<td>0.7709924</td>
	<td>0.0423054</td>
	<td>0.0423054</td>
	<td>322.9090447</td>
	<td>322.9090447</td></tr>
	<tr><td></td>
	<td>2</td>
	<td>0.0200069</td>
	<td>0.5350310</td>
	<td>3.4879528</td>
	<td>3.8585216</td>
	<td>0.6358779</td>
	<td>0.7034351</td>
	<td>0.0348915</td>
	<td>0.0771970</td>
	<td>248.7952815</td>
	<td>285.8521631</td></tr>
	<tr><td></td>
	<td>3</td>
	<td>0.0300027</td>
	<td>0.5007744</td>
	<td>3.1972882</td>
	<td>3.6382227</td>
	<td>0.5828877</td>
	<td>0.6632731</td>
	<td>0.0319595</td>
	<td>0.1091564</td>
	<td>219.7288214</td>
	<td>263.8222689</td></tr>
	<tr><td></td>
	<td>4</td>
	<td>0.0400061</td>
	<td>0.4718430</td>
	<td>2.9436144</td>
	<td>3.4645375</td>
	<td>0.5366412</td>
	<td>0.6316091</td>
	<td>0.0294463</td>
	<td>0.1386027</td>
	<td>194.3614440</td>
	<td>246.4537481</td></tr>
	<tr><td></td>
	<td>5</td>
	<td>0.0500019</td>
	<td>0.4483865</td>
	<td>2.8704357</td>
	<td>3.3457716</td>
	<td>0.5233002</td>
	<td>0.6099572</td>
	<td>0.0286923</td>
	<td>0.1672950</td>
	<td>187.0435684</td>
	<td>234.5771560</td></tr>
	<tr><td></td>
	<td>6</td>
	<td>0.1000038</td>
	<td>0.3623038</td>
	<td>2.4444070</td>
	<td>2.8950893</td>
	<td>0.4456323</td>
	<td>0.5277947</td>
	<td>0.1222250</td>
	<td>0.2895200</td>
	<td>144.4406963</td>
	<td>189.5089261</td></tr>
	<tr><td></td>
	<td>7</td>
	<td>0.1500057</td>
	<td>0.3079302</td>
	<td>1.9878608</td>
	<td>2.5926798</td>
	<td>0.3624007</td>
	<td>0.4726634</td>
	<td>0.0993968</td>
	<td>0.3889168</td>
	<td>98.7860769</td>
	<td>159.2679764</td></tr>
	<tr><td></td>
	<td>8</td>
	<td>0.2</td>
	<td>0.2684456</td>
	<td>1.7116814</td>
	<td>2.3724554</td>
	<td>0.3120513</td>
	<td>0.4325150</td>
	<td>0.0855743</td>
	<td>0.4744911</td>
	<td>71.1681359</td>
	<td>137.2455391</td></tr>
	<tr><td></td>
	<td>9</td>
	<td>0.3000038</td>
	<td>0.2132009</td>
	<td>1.4102670</td>
	<td>2.0517178</td>
	<td>0.2571014</td>
	<td>0.3740423</td>
	<td>0.1410321</td>
	<td>0.6155232</td>
	<td>41.0267006</td>
	<td>105.1717765</td></tr>
	<tr><td></td>
	<td>10</td>
	<td>0.4</td>
	<td>0.1765625</td>
	<td>1.1217652</td>
	<td>1.8192385</td>
	<td>0.2045055</td>
	<td>0.3316597</td>
	<td>0.1121722</td>
	<td>0.7276954</td>
	<td>12.1765206</td>
	<td>81.9238502</td></tr>
	<tr><td></td>
	<td>11</td>
	<td>0.5000038</td>
	<td>0.1503145</td>
	<td>0.8745582</td>
	<td>1.6302967</td>
	<td>0.1594380</td>
	<td>0.2972143</td>
	<td>0.0874592</td>
	<td>0.8151546</td>
	<td>-12.5441786</td>
	<td>63.0296674</td></tr>
	<tr><td></td>
	<td>12</td>
	<td>0.6</td>
	<td>0.1300345</td>
	<td>0.6769128</td>
	<td>1.4714054</td>
	<td>0.1234059</td>
	<td>0.2682474</td>
	<td>0.0676887</td>
	<td>0.8828433</td>
	<td>-32.3087165</td>
	<td>47.1405434</td></tr>
	<tr><td></td>
	<td>13</td>
	<td>0.6999962</td>
	<td>0.1129563</td>
	<td>0.4959559</td>
	<td>1.3320601</td>
	<td>0.0904162</td>
	<td>0.2428437</td>
	<td>0.0495937</td>
	<td>0.9324370</td>
	<td>-50.4044061</td>
	<td>33.2060067</td></tr>
	<tr><td></td>
	<td>14</td>
	<td>0.8</td>
	<td>0.0978849</td>
	<td>0.3920433</td>
	<td>1.2145535</td>
	<td>0.0714722</td>
	<td>0.2214215</td>
	<td>0.0392058</td>
	<td>0.9716428</td>
	<td>-60.7956663</td>
	<td>21.4553489</td></tr>
	<tr><td></td>
	<td>15</td>
	<td>0.8999962</td>
	<td>0.0824531</td>
	<td>0.2194940</td>
	<td>1.1039951</td>
	<td>0.0400153</td>
	<td>0.2012659</td>
	<td>0.0219486</td>
	<td>0.9935914</td>
	<td>-78.0505987</td>
	<td>10.3995078</td></tr>
	<tr><td></td>
	<td>16</td>
	<td>1.0</td>
	<td>0.0597755</td>
	<td>0.0640840</td>
	<td>1.0</td>
	<td>0.0116830</td>
	<td>0.1823069</td>
	<td>0.0064086</td>
	<td>1.0</td>
	<td>-93.5915993</td>
	<td>0.0</td></tr></table></div>
	</div>

	</div>

	<div class="output_area">
	<div class="prompt"></div>

	<div class="output_subarea output_stream output_stdout output_text">
	<pre>

	ModelMetricsBinomialGLM: stackedensemble
	Reported on validation data.

	MSE: 0.13813682407268132
	RMSE: 0.37166762580655494
	LogLoss: 0.4379927029517987
	Null degrees of freedom: 33031
	Residual degrees of freedom: 33020
	Null deviance: 31732.354674481932
	Residual deviance: 28935.54992780763
	AIC: 28959.54992780763
	AUC: 0.7122628231156057
	Gini: 0.4245256462312115
	Confusion Matrix (Act/Pred) for max f1 @ threshold = 0.18933454821029921:
	</pre>
	</div>
	</div>

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	<div class="output_html rendered_html output_subarea ">
	<div style="overflow:auto"><table style="width:50%"><tr><td><b></b></td>
	<td><b>0</b></td>
	<td><b>1</b></td>
	<td><b>Error</b></td>
	<td><b>Rate</b></td></tr>
	<tr><td>0</td>
	<td>18652.0</td>
	<td>8238.0</td>
	<td>0.3064</td>
	<td> (8238.0/26890.0)</td></tr>
	<tr><td>1</td>
	<td>2386.0</td>
	<td>3756.0</td>
	<td>0.3885</td>
	<td> (2386.0/6142.0)</td></tr>
	<tr><td>Total</td>
	<td>21038.0</td>
	<td>11994.0</td>
	<td>0.3216</td>
	<td> (10624.0/33032.0)</td></tr></table></div>
	</div>

	</div>

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	<div class="output_subarea output_stream output_stdout output_text">
	<pre>Maximum Metrics: Maximum metrics at their respective thresholds

	</pre>
	</div>
	</div>

	<div class="output_area">
	<div class="prompt"></div>


	<div class="output_html rendered_html output_subarea ">
	<div style="overflow:auto"><table style="width:50%"><tr><td><b>metric</b></td>
	<td><b>threshold</b></td>
	<td><b>value</b></td>
	<td><b>idx</b></td></tr>
	<tr><td>max f1</td>
	<td>0.1893345</td>
	<td>0.4142038</td>
	<td>256.0</td></tr>
	<tr><td>max f2</td>
	<td>0.1197407</td>
	<td>0.5738535</td>
	<td>330.0</td></tr>
	<tr><td>max f0point5</td>
	<td>0.3129965</td>
	<td>0.3817812</td>
	<td>160.0</td></tr>
	<tr><td>max accuracy</td>
	<td>0.6010242</td>
	<td>0.8160572</td>
	<td>29.0</td></tr>
	<tr><td>max precision</td>
	<td>0.7666583</td>
	<td>1.0</td>
	<td>0.0</td></tr>
	<tr><td>max recall</td>
	<td>0.0640080</td>
	<td>1.0</td>
	<td>398.0</td></tr>
	<tr><td>max specificity</td>
	<td>0.7666583</td>
	<td>1.0</td>
	<td>0.0</td></tr>
	<tr><td>max absolute_mcc</td>
	<td>0.2092723</td>
	<td>0.2475688</td>
	<td>238.0</td></tr>
	<tr><td>max min_per_class_accuracy</td>
	<td>0.1762849</td>
	<td>0.6525562</td>
	<td>268.0</td></tr>
	<tr><td>max mean_per_class_accuracy</td>
	<td>0.1577331</td>
	<td>0.6547886</td>
	<td>286.0</td></tr></table></div>
	</div>

	</div>

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	<pre>Gains/Lift Table: Avg response rate: 18.59 %

	</pre>
	</div>
	</div>

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	<div class="output_html rendered_html output_subarea ">
	<div style="overflow:auto"><table style="width:50%"><tr><td><b></b></td>
	<td><b>group</b></td>
	<td><b>cumulative_data_fraction</b></td>
	<td><b>lower_threshold</b></td>
	<td><b>lift</b></td>
	<td><b>cumulative_lift</b></td>
	<td><b>response_rate</b></td>
	<td><b>cumulative_response_rate</b></td>
	<td><b>capture_rate</b></td>
	<td><b>cumulative_capture_rate</b></td>
	<td><b>gain</b></td>
	<td><b>cumulative_gain</b></td></tr>
	<tr><td></td>
	<td>1</td>
	<td>0.0100206</td>
	<td>0.5783690</td>
	<td>3.1358434</td>
	<td>3.1358434</td>
	<td>0.5830816</td>
	<td>0.5830816</td>
	<td>0.0314230</td>
	<td>0.0314230</td>
	<td>213.5843447</td>
	<td>213.5843447</td></tr>
	<tr><td></td>
	<td>2</td>
	<td>0.0200109</td>
	<td>0.5293169</td>
	<td>2.5749465</td>
	<td>2.8558192</td>
	<td>0.4787879</td>
	<td>0.5310136</td>
	<td>0.0257245</td>
	<td>0.0571475</td>
	<td>157.4946469</td>
	<td>185.5819237</td></tr>
	<tr><td></td>
	<td>3</td>
	<td>0.0300012</td>
	<td>0.4955180</td>
	<td>2.4119752</td>
	<td>2.7080205</td>
	<td>0.4484848</td>
	<td>0.5035318</td>
	<td>0.0240964</td>
	<td>0.0812439</td>
	<td>141.1975173</td>
	<td>170.8020508</td></tr>
	<tr><td></td>
	<td>4</td>
	<td>0.0400218</td>
	<td>0.4688250</td>
	<td>2.4859277</td>
	<td>2.6524133</td>
	<td>0.4622356</td>
	<td>0.4931921</td>
	<td>0.0249105</td>
	<td>0.1061543</td>
	<td>148.5927707</td>
	<td>165.2413309</td></tr>
	<tr><td></td>
	<td>5</td>
	<td>0.0500121</td>
	<td>0.4455599</td>
	<td>2.2164096</td>
	<td>2.5653181</td>
	<td>0.4121212</td>
	<td>0.4769976</td>
	<td>0.0221426</td>
	<td>0.1282970</td>
	<td>121.6409619</td>
	<td>156.5318141</td></tr>
	<tr><td></td>
	<td>6</td>
	<td>0.1000242</td>
	<td>0.3612868</td>
	<td>2.0607188</td>
	<td>2.3130185</td>
	<td>0.3831719</td>
	<td>0.4300847</td>
	<td>0.1030609</td>
	<td>0.2313579</td>
	<td>106.0718760</td>
	<td>131.3018450</td></tr>
	<tr><td></td>
	<td>7</td>
	<td>0.1500061</td>
	<td>0.3068785</td>
	<td>1.7850835</td>
	<td>2.1371112</td>
	<td>0.3319200</td>
	<td>0.3973764</td>
	<td>0.0892218</td>
	<td>0.3205796</td>
	<td>78.5083530</td>
	<td>113.7111174</td></tr>
	<tr><td></td>
	<td>8</td>
	<td>0.2000182</td>
	<td>0.2675737</td>
	<td>1.5756523</td>
	<td>1.9967252</td>
	<td>0.2929782</td>
	<td>0.3712729</td>
	<td>0.0788017</td>
	<td>0.3993813</td>
	<td>57.5652259</td>
	<td>99.6725200</td></tr>
	<tr><td></td>
	<td>9</td>
	<td>0.3000121</td>
	<td>0.2132448</td>
	<td>1.3758567</td>
	<td>1.7897899</td>
	<td>0.2558280</td>
	<td>0.3327952</td>
	<td>0.1375773</td>
	<td>0.5369586</td>
	<td>37.5856668</td>
	<td>78.9789907</td></tr>
	<tr><td></td>
	<td>10</td>
	<td>0.4000061</td>
	<td>0.1764937</td>
	<td>1.1299935</td>
	<td>1.6248533</td>
	<td>0.2101120</td>
	<td>0.3021267</td>
	<td>0.1129925</td>
	<td>0.6499512</td>
	<td>12.9993524</td>
	<td>62.4853295</td></tr>
	<tr><td></td>
	<td>11</td>
	<td>0.5</td>
	<td>0.1497263</td>
	<td>0.9964784</td>
	<td>1.4991859</td>
	<td>0.1852861</td>
	<td>0.2787600</td>
	<td>0.0996418</td>
	<td>0.7495930</td>
	<td>-0.3521561</td>
	<td>49.9185933</td></tr>
	<tr><td></td>
	<td>12</td>
	<td>0.5999939</td>
	<td>0.1296393</td>
	<td>0.7587565</td>
	<td>1.3757872</td>
	<td>0.1410839</td>
	<td>0.2558151</td>
	<td>0.0758711</td>
	<td>0.8254640</td>
	<td>-24.1243542</td>
	<td>37.5787247</td></tr>
	<tr><td></td>
	<td>13</td>
	<td>0.6999879</td>
	<td>0.1130667</td>
	<td>0.6284978</td>
	<td>1.2690362</td>
	<td>0.1168635</td>
	<td>0.2359657</td>
	<td>0.0628460</td>
	<td>0.8883100</td>
	<td>-37.1502161</td>
	<td>26.9036234</td></tr>
	<tr><td></td>
	<td>14</td>
	<td>0.7999818</td>
	<td>0.0982229</td>
	<td>0.5259192</td>
	<td>1.1761501</td>
	<td>0.0977899</td>
	<td>0.2186944</td>
	<td>0.0525887</td>
	<td>0.9408987</td>
	<td>-47.4080824</td>
	<td>17.6150117</td></tr>
	<tr><td></td>
	<td>15</td>
	<td>0.8999758</td>
	<td>0.0826149</td>
	<td>0.3989170</td>
	<td>1.0897938</td>
	<td>0.0741750</td>
	<td>0.2026372</td>
	<td>0.0398893</td>
	<td>0.9807880</td>
	<td>-60.1082978</td>
	<td>8.9793790</td></tr>
	<tr><td></td>
	<td>16</td>
	<td>1.0</td>
	<td>0.0605773</td>
	<td>0.1920733</td>
	<td>1.0</td>
	<td>0.0357143</td>
	<td>0.1859409</td>
	<td>0.0192120</td>
	<td>1.0</td>
	<td>-80.7926687</td>
	<td>0.0</td></tr></table></div>
	</div>

	</div>

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	<pre>

	ModelMetricsBinomialGLM: stackedensemble
	Reported on cross-validation data.

	MSE: 0.1369765435568584
	RMSE: 0.3701034227845757
	LogLoss: 0.4355309009590542
	Null degrees of freedom: 130954
	Residual degrees of freedom: 130943
	Null deviance: 124375.46514588114
	Residual deviance: 114069.89827018589
	AIC: 114093.89827018589
	AUC: 0.7071203432205223
	Gini: 0.4142406864410446
	Confusion Matrix (Act/Pred) for max f1 @ threshold = 0.17843972441369682:
	</pre>
	</div>
	</div>

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	<div class="output_html rendered_html output_subarea ">
	<div style="overflow:auto"><table style="width:50%"><tr><td><b></b></td>
	<td><b>0</b></td>
	<td><b>1</b></td>
	<td><b>Error</b></td>
	<td><b>Rate</b></td></tr>
	<tr><td>0</td>
	<td>73561.0</td>
	<td>33520.0</td>
	<td>0.313</td>
	<td> (33520.0/107081.0)</td></tr>
	<tr><td>1</td>
	<td>9215.0</td>
	<td>14659.0</td>
	<td>0.386</td>
	<td> (9215.0/23874.0)</td></tr>
	<tr><td>Total</td>
	<td>82776.0</td>
	<td>48179.0</td>
	<td>0.3263</td>
	<td> (42735.0/130955.0)</td></tr></table></div>
	</div>

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	<pre>Maximum Metrics: Maximum metrics at their respective thresholds

	</pre>
	</div>
	</div>

	<div class="output_area">
	<div class="prompt"></div>


	<div class="output_html rendered_html output_subarea ">
	<div style="overflow:auto"><table style="width:50%"><tr><td><b>metric</b></td>
	<td><b>threshold</b></td>
	<td><b>value</b></td>
	<td><b>idx</b></td></tr>
	<tr><td>max f1</td>
	<td>0.1784397</td>
	<td>0.4068949</td>
	<td>261.0</td></tr>
	<tr><td>max f2</td>
	<td>0.1136746</td>
	<td>0.5665672</td>
	<td>334.0</td></tr>
	<tr><td>max f0point5</td>
	<td>0.2879939</td>
	<td>0.3708050</td>
	<td>176.0</td></tr>
	<tr><td>max accuracy</td>
	<td>0.5663591</td>
	<td>0.8184567</td>
	<td>36.0</td></tr>
	<tr><td>max precision</td>
	<td>0.7859236</td>
	<td>1.0</td>
	<td>0.0</td></tr>
	<tr><td>max recall</td>
	<td>0.0620870</td>
	<td>1.0</td>
	<td>399.0</td></tr>
	<tr><td>max specificity</td>
	<td>0.7859236</td>
	<td>1.0</td>
	<td>0.0</td></tr>
	<tr><td>max absolute_mcc</td>
	<td>0.1815977</td>
	<td>0.2412252</td>
	<td>258.0</td></tr>
	<tr><td>max min_per_class_accuracy</td>
	<td>0.1671726</td>
	<td>0.6498819</td>
	<td>272.0</td></tr>
	<tr><td>max mean_per_class_accuracy</td>
	<td>0.1616542</td>
	<td>0.6512829</td>
	<td>278.0</td></tr></table></div>
	</div>

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	<pre>Gains/Lift Table: Avg response rate: 18.23 %

	</pre>
	</div>
	</div>

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	<div style="overflow:auto"><table style="width:50%"><tr><td><b></b></td>
	<td><b>group</b></td>
	<td><b>cumulative_data_fraction</b></td>
	<td><b>lower_threshold</b></td>
	<td><b>lift</b></td>
	<td><b>cumulative_lift</b></td>
	<td><b>response_rate</b></td>
	<td><b>cumulative_response_rate</b></td>
	<td><b>capture_rate</b></td>
	<td><b>cumulative_capture_rate</b></td>
	<td><b>gain</b></td>
	<td><b>cumulative_gain</b></td></tr>
	<tr><td></td>
	<td>1</td>
	<td>0.0100034</td>
	<td>0.5609815</td>
	<td>2.9394272</td>
	<td>2.9394272</td>
	<td>0.5358779</td>
	<td>0.5358779</td>
	<td>0.0294044</td>
	<td>0.0294044</td>
	<td>193.9427222</td>
	<td>193.9427222</td></tr>
	<tr><td></td>
	<td>2</td>
	<td>0.0200069</td>
	<td>0.5136764</td>
	<td>2.6044498</td>
	<td>2.7719385</td>
	<td>0.4748092</td>
	<td>0.5053435</td>
	<td>0.0260534</td>
	<td>0.0554578</td>
	<td>160.4449761</td>
	<td>177.1938491</td></tr>
	<tr><td></td>
	<td>3</td>
	<td>0.0300027</td>
	<td>0.4802174</td>
	<td>2.4346323</td>
	<td>2.6595603</td>
	<td>0.4438503</td>
	<td>0.4848562</td>
	<td>0.0243361</td>
	<td>0.0797939</td>
	<td>143.4632310</td>
	<td>165.9560331</td></tr>
	<tr><td></td>
	<td>4</td>
	<td>0.0400061</td>
	<td>0.4541967</td>
	<td>2.2987828</td>
	<td>2.5693487</td>
	<td>0.4190840</td>
	<td>0.4684100</td>
	<td>0.0229957</td>
	<td>0.1027896</td>
	<td>129.8782827</td>
	<td>156.9348739</td></tr>
	<tr><td></td>
	<td>5</td>
	<td>0.0500019</td>
	<td>0.4304407</td>
	<td>2.3592048</td>
	<td>2.5273392</td>
	<td>0.4300993</td>
	<td>0.4607514</td>
	<td>0.0235821</td>
	<td>0.1263718</td>
	<td>135.9204803</td>
	<td>152.7339208</td></tr>
	<tr><td></td>
	<td>6</td>
	<td>0.1000038</td>
	<td>0.3489922</td>
	<td>2.0674422</td>
	<td>2.2973907</td>
	<td>0.3769090</td>
	<td>0.4188302</td>
	<td>0.1033761</td>
	<td>0.2297478</td>
	<td>106.7442216</td>
	<td>129.7390712</td></tr>
	<tr><td></td>
	<td>7</td>
	<td>0.1500057</td>
	<td>0.2957391</td>
	<td>1.7583311</td>
	<td>2.1177042</td>
	<td>0.3205559</td>
	<td>0.3860721</td>
	<td>0.0879199</td>
	<td>0.3176678</td>
	<td>75.8331123</td>
	<td>111.7704182</td></tr>
	<tr><td></td>
	<td>8</td>
	<td>0.2</td>
	<td>0.2569097</td>
	<td>1.5826559</td>
	<td>1.9839574</td>
	<td>0.2885291</td>
	<td>0.3616891</td>
	<td>0.0791237</td>
	<td>0.3967915</td>
	<td>58.2655941</td>
	<td>98.3957443</td></tr>
	<tr><td></td>
	<td>9</td>
	<td>0.3000038</td>
	<td>0.2032167</td>
	<td>1.3679632</td>
	<td>1.7786208</td>
	<td>0.2493891</td>
	<td>0.3242548</td>
	<td>0.1368015</td>
	<td>0.5335930</td>
	<td>36.7963184</td>
	<td>77.8620797</td></tr>
	<tr><td></td>
	<td>10</td>
	<td>0.4</td>
	<td>0.1679941</td>
	<td>1.1284673</td>
	<td>1.6160886</td>
	<td>0.2057274</td>
	<td>0.2946241</td>
	<td>0.1128424</td>
	<td>0.6464355</td>
	<td>12.8467313</td>
	<td>61.6088632</td></tr>
	<tr><td></td>
	<td>11</td>
	<td>0.5000038</td>
	<td>0.1428590</td>
	<td>0.9302652</td>
	<td>1.4789198</td>
	<td>0.1695938</td>
	<td>0.2696173</td>
	<td>0.0930301</td>
	<td>0.7394655</td>
	<td>-6.9734773</td>
	<td>47.8919761</td></tr>
	<tr><td></td>
	<td>12</td>
	<td>0.6</td>
	<td>0.1238863</td>
	<td>0.8143060</td>
	<td>1.3681550</td>
	<td>0.1484536</td>
	<td>0.2494241</td>
	<td>0.0814275</td>
	<td>0.8208930</td>
	<td>-18.5693965</td>
	<td>36.8155036</td></tr>
	<tr><td></td>
	<td>13</td>
	<td>0.6999962</td>
	<td>0.1081113</td>
	<td>0.6589009</td>
	<td>1.2668363</td>
	<td>0.1201222</td>
	<td>0.2309530</td>
	<td>0.0658876</td>
	<td>0.8867806</td>
	<td>-34.1099078</td>
	<td>26.6836336</td></tr>
	<tr><td></td>
	<td>14</td>
	<td>0.8</td>
	<td>0.0941428</td>
	<td>0.5185360</td>
	<td>1.1732952</td>
	<td>0.0945327</td>
	<td>0.2138998</td>
	<td>0.0518556</td>
	<td>0.9386362</td>
	<td>-48.1464047</td>
	<td>17.3295217</td></tr>
	<tr><td></td>
	<td>15</td>
	<td>0.8999962</td>
	<td>0.0801775</td>
	<td>0.3945866</td>
	<td>1.0867750</td>
	<td>0.0719359</td>
	<td>0.1981266</td>
	<td>0.0394572</td>
	<td>0.9780933</td>
	<td>-60.5413434</td>
	<td>8.6774970</td></tr>
	<tr><td></td>
	<td>16</td>
	<td>1.0</td>
	<td>0.0597666</td>
	<td>0.2190584</td>
	<td>1.0</td>
	<td>0.0399359</td>
	<td>0.1823069</td>
	<td>0.0219067</td>
	<td>1.0</td>
	<td>-78.0941597</td>
	<td>0.0</td></tr></table></div>
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	<pre></pre>
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	<div class=" highlight hl-ipython3"><pre><span></span><span class="n">aml</span><span class="o">.</span><span class="n">leader</span><span class="o">.</span><span class="n">algo</span>
	</pre></div>

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	<pre>'stackedensemble'</pre>
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	</div>
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	<div class=" highlight hl-ipython3"><pre><span></span><span class="nb">dir</span><span class="p">(</span><span class="n">aml</span><span class="o">.</span><span class="n">leader</span><span class="p">)</span>
	</pre></div>

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	<pre>['F0point5',
	'F1',
	'F2',
	'__class__',
	'__delattr__',
	'__dict__',
	'__dir__',
	'__doc__',
	'__eq__',
	'__format__',
	'__ge__',
	'__getattr__',
	'__getattribute__',
	'__gt__',
	'__hash__',
	'__init__',
	'__init_subclass__',
	'__le__',
	'__lt__',
	'__module__',
	'__ne__',
	'__new__',
	'__reduce__',
	'__reduce_ex__',
	'__repr__',
	'__setattr__',
	'__sizeof__',
	'__str__',
	'__subclasshook__',
	'__weakref__',
	'_bc',
	'_bcin',
	'_check_targets',
	'_compute_algo',
	'_estimator_type',
	'_future',
	'_get_metrics',
	'_have_mojo',
	'_have_pojo',
	'_id',
	'_is_xvalidated',
	'_job',
	'_keyify_if_h2oframe',
	'_metrics_class',
	'_model_json',
	'_parms',
	'_plot',
	'_requires_training_frame',
	'_resolve_model',
	'_verify_training_frame_params',
	'_xval_keys',
	'accuracy',
	'actual_params',
	'aic',
	'algo',
	'auc',
	'base_models',
	'biases',
	'catoffsets',
	'coef',
	'coef_norm',
	'confusion_matrix',
	'cross_validation_fold_assignment',
	'cross_validation_holdout_predictions',
	'cross_validation_metrics_summary',
	'cross_validation_models',
	'cross_validation_predictions',
	'deepfeatures',
	'default_params',
	'download_mojo',
	'download_pojo',
	'error',
	'fallout',
	'find_idx_by_threshold',
	'find_threshold_by_max_metric',
	'fit',
	'fnr',
	'fpr',
	'full_parameters',
	'gains_lift',
	'get_params',
	'get_xval_models',
	'gini',
	'have_mojo',
	'have_pojo',
	'is_cross_validated',
	'join',
	'keep_levelone_frame',
	'levelone_frame_id',
	'logloss',
	'mae',
	'max_per_class_error',
	'mcc',
	'mean_per_class_error',
	'mean_residual_deviance',
	'metalearner',
	'metalearner_algorithm',
	'metalearner_fold_assignment',
	'metalearner_fold_column',
	'metalearner_nfolds',
	'metalearner_params',
	'metric',
	'missrate',
	'mixin',
	'model_id',
	'model_performance',
	'mse',
	'normmul',
	'normsub',
	'null_degrees_of_freedom',
	'null_deviance',
	'params',
	'parms',
	'partial_plot',
	'plot',
	'pprint_coef',
	'precision',
	'predict',
	'predict_leaf_node_assignment',
	'r2',
	'recall',
	'residual_degrees_of_freedom',
	'residual_deviance',
	'respmul',
	'response_column',
	'respsub',
	'rmse',
	'rmsle',
	'roc',
	'rotation',
	'save_model_details',
	'save_mojo',
	'score_history',
	'scoring_history',
	'seed',
	'sensitivity',
	'set_params',
	'show',
	'specificity',
	'start',
	'std_coef_plot',
	'summary',
	'tnr',
	'tpr',
	'train',
	'training_frame',
	'type',
	'validation_frame',
	'varimp',
	'varimp_plot',
	'weights',
	'xval_keys',
	'xvals']</pre>
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	<h2 id="Ensemble-Exploration">Ensemble Exploration<a class="anchor-link" href="#Ensemble-Exploration">¶</a></h2><p>To understand how the ensemble works, let's take a peek inside the Stacked Ensemble "All Models" model. The "All Models" ensemble is an ensemble of all of the individual models in the AutoML run. This is often the top performing model on the leaderboard.</p>

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	<div class=" highlight hl-ipython3"><pre><span></span><span class="n">aml_leaderboard_df</span><span class="o">=</span><span class="n">aml</span><span class="o">.</span><span class="n">leaderboard</span><span class="o">.</span><span class="n">as_data_frame</span><span class="p">()</span>
	<span class="n">aml_leaderboard_df</span>
	</pre></div>

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	<style>
	.dataframe thead tr:only-child th {
	text-align: right;
	}

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	}

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	vertical-align: top;
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	</style>
	<table border="1" class="dataframe">
	<thead>
	<tr style="text-align: right;">
	<th></th>
	<th>model_id</th>
	<th>auc</th>
	<th>logloss</th>
	<th>mean_per_class_error</th>
	<th>rmse</th>
	<th>mse</th>
	</tr>
	</thead>
	<tbody>
	<tr>
	<th>0</th>
	<td>StackedEnsemble_AllModels_0_AutoML_20181120_15...</td>
	<td>0.707120</td>
	<td>0.435531</td>
	<td>0.349509</td>
	<td>0.370103</td>
	<td>0.136977</td>
	</tr>
	<tr>
	<th>1</th>
	<td>StackedEnsemble_AllModels_0_AutoML_20181120_15...</td>
	<td>0.706222</td>
	<td>0.435883</td>
	<td>0.351685</td>
	<td>0.370262</td>
	<td>0.137094</td>
	</tr>
	<tr>
	<th>2</th>
	<td>StackedEnsemble_BestOfFamily_0_AutoML_20181120...</td>
	<td>0.705212</td>
	<td>0.436220</td>
	<td>0.350829</td>
	<td>0.370407</td>
	<td>0.137202</td>
	</tr>
	<tr>
	<th>3</th>
	<td>GBM_grid_0_AutoML_20181120_154205_model_0</td>
	<td>0.703839</td>
	<td>0.435055</td>
	<td>0.353507</td>
	<td>0.370225</td>
	<td>0.137067</td>
	</tr>
	<tr>
	<th>4</th>
	<td>GBM_grid_0_AutoML_20181120_153506_model_0</td>
	<td>0.703216</td>
	<td>0.435227</td>
	<td>0.352786</td>
	<td>0.370273</td>
	<td>0.137102</td>
	</tr>
	<tr>
	<th>5</th>
	<td>GBM_grid_0_AutoML_20181120_153506_model_1</td>
	<td>0.702313</td>
	<td>0.435862</td>
	<td>0.353887</td>
	<td>0.370509</td>
	<td>0.137277</td>
	</tr>
	<tr>
	<th>6</th>
	<td>GBM_grid_0_AutoML_20181120_154205_model_1</td>
	<td>0.702177</td>
	<td>0.435943</td>
	<td>0.354178</td>
	<td>0.370554</td>
	<td>0.137310</td>
	</tr>
	<tr>
	<th>7</th>
	<td>GBM_grid_0_AutoML_20181120_153506_model_2</td>
	<td>0.700280</td>
	<td>0.437029</td>
	<td>0.354784</td>
	<td>0.370872</td>
	<td>0.137546</td>
	</tr>
	<tr>
	<th>8</th>
	<td>GBM_grid_0_AutoML_20181120_154205_model_2</td>
	<td>0.699971</td>
	<td>0.437370</td>
	<td>0.354552</td>
	<td>0.371075</td>
	<td>0.137696</td>
	</tr>
	<tr>
	<th>9</th>
	<td>DeepLearning_0_AutoML_20181120_154205</td>
	<td>0.699148</td>
	<td>0.439850</td>
	<td>0.355085</td>
	<td>0.372547</td>
	<td>0.138791</td>
	</tr>
	<tr>
	<th>10</th>
	<td>GLM_grid_0_AutoML_20181120_154205_model_0</td>
	<td>0.697503</td>
	<td>0.438455</td>
	<td>0.354668</td>
	<td>0.371441</td>
	<td>0.137968</td>
	</tr>
	<tr>
	<th>11</th>
	<td>GLM_grid_0_AutoML_20181120_153506_model_0</td>
	<td>0.697503</td>
	<td>0.438455</td>
	<td>0.354668</td>
	<td>0.371441</td>
	<td>0.137968</td>
	</tr>
	<tr>
	<th>12</th>
	<td>DeepLearning_0_AutoML_20181120_153506</td>
	<td>0.696297</td>
	<td>0.439618</td>
	<td>0.357903</td>
	<td>0.371964</td>
	<td>0.138357</td>
	</tr>
	<tr>
	<th>13</th>
	<td>GBM_grid_0_AutoML_20181120_154205_model_4</td>
	<td>0.694225</td>
	<td>0.443191</td>
	<td>0.361761</td>
	<td>0.372926</td>
	<td>0.139073</td>
	</tr>
	<tr>
	<th>14</th>
	<td>GBM_grid_0_AutoML_20181120_153506_model_4</td>
	<td>0.694205</td>
	<td>0.442884</td>
	<td>0.358243</td>
	<td>0.372862</td>
	<td>0.139026</td>
	</tr>
	<tr>
	<th>15</th>
	<td>GBM_grid_0_AutoML_20181120_153506_model_3</td>
	<td>0.690842</td>
	<td>0.443542</td>
	<td>0.362873</td>
	<td>0.373139</td>
	<td>0.139233</td>
	</tr>
	<tr>
	<th>16</th>
	<td>GBM_grid_0_AutoML_20181120_154205_model_3</td>
	<td>0.689891</td>
	<td>0.443962</td>
	<td>0.363898</td>
	<td>0.373311</td>
	<td>0.139361</td>
	</tr>
	<tr>
	<th>17</th>
	<td>XRT_0_AutoML_20181120_154205</td>
	<td>0.688110</td>
	<td>0.471744</td>
	<td>0.364619</td>
	<td>0.382286</td>
	<td>0.146143</td>
	</tr>
	<tr>
	<th>18</th>
	<td>XRT_0_AutoML_20181120_153506</td>
	<td>0.687225</td>
	<td>0.472021</td>
	<td>0.365550</td>
	<td>0.382442</td>
	<td>0.146262</td>
	</tr>
	<tr>
	<th>19</th>
	<td>DRF_0_AutoML_20181120_154205</td>
	<td>0.684609</td>
	<td>0.479048</td>
	<td>0.366846</td>
	<td>0.383622</td>
	<td>0.147166</td>
	</tr>
	<tr>
	<th>20</th>
	<td>DRF_0_AutoML_20181120_153506</td>
	<td>0.684478</td>
	<td>0.479350</td>
	<td>0.367447</td>
	<td>0.383614</td>
	<td>0.147160</td>
	</tr>
	<tr>
	<th>21</th>
	<td>DRF_0_AutoML_20181120_153207</td>
	<td>0.683488</td>
	<td>0.479453</td>
	<td>0.368185</td>
	<td>0.383608</td>
	<td>0.147155</td>
	</tr>
	</tbody>
	</table>
	</div>
	</div>

	</div>

	</div>
	</div>

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	<h2 id="Getting-models">Getting models<a class="anchor-link" href="#Getting-models">¶</a></h2><p>Individul models can ne found through a search of the leader board or directly by the name.</p>

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	<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Get model ids for all models in the AutoML Leaderboard</span>
	<span class="n">model_ids</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="n">aml</span><span class="o">.</span><span class="n">leaderboard</span><span class="p">[</span><span class="s1">'model_id'</span><span class="p">]</span><span class="o">.</span><span class="n">as_data_frame</span><span class="p">()</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:,</span><span class="mi">0</span><span class="p">])</span>
	<span class="c1"># Get the "All Models" Stacked Ensemble model</span>
	<span class="n">se</span> <span class="o">=</span> <span class="n">h2o</span><span class="o">.</span><span class="n">get_model</span><span class="p">([</span><span class="n">mid</span> <span class="k">for</span> <span class="n">mid</span> <span class="ow">in</span> <span class="n">model_ids</span> <span class="k">if</span> <span class="s2">"StackedEnsemble_AllModels"</span> <span class="ow">in</span> <span class="n">mid</span><span class="p">][</span><span class="mi">0</span><span class="p">])</span>
	<span class="c1"># Get the Stacked Ensemble metalearner model</span>
	<span class="n">metalearner</span> <span class="o">=</span> <span class="n">h2o</span><span class="o">.</span><span class="n">get_model</span><span class="p">(</span><span class="n">aml</span><span class="o">.</span><span class="n">leader</span><span class="o">.</span><span class="n">metalearner</span><span class="p">()[</span><span class="s1">'name'</span><span class="p">])</span>
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	<div class=" highlight hl-ipython3"><pre><span></span><span class="n">metalearner</span><span class="o">.</span><span class="n">coef_norm</span><span class="p">()</span>
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	<pre>{'DRF_0_AutoML_20181120_153207': 0.0,
	'DRF_0_AutoML_20181120_153506': 0.0,
	'DRF_0_AutoML_20181120_154205': 0.0,
	'DeepLearning_0_AutoML_20181120_153506': 0.1344838464922838,
	'DeepLearning_0_AutoML_20181120_154205': 0.16114849497175607,
	'GBM_grid_0_AutoML_20181120_153506_model_0': 0.06857343556357838,
	'GBM_grid_0_AutoML_20181120_153506_model_1': 0.06556630998879215,
	'GBM_grid_0_AutoML_20181120_153506_model_2': 0.06399896524231677,
	'GBM_grid_0_AutoML_20181120_153506_model_3': 0.0,
	'GBM_grid_0_AutoML_20181120_153506_model_4': 0.029475852258499607,
	'GBM_grid_0_AutoML_20181120_154205_model_0': 0.10436142902876248,
	'GBM_grid_0_AutoML_20181120_154205_model_1': 0.030089245243887962,
	'GBM_grid_0_AutoML_20181120_154205_model_2': 0.024832084306272362,
	'GBM_grid_0_AutoML_20181120_154205_model_3': 0.0,
	'GBM_grid_0_AutoML_20181120_154205_model_4': 0.03820562737398706,
	'GLM_grid_0_AutoML_20181120_153506_model_0': 0.0,
	'GLM_grid_0_AutoML_20181120_154205_model_0': 0.0,
	'Intercept': -1.648080783111384,
	'XRT_0_AutoML_20181120_153506': 0.0,
	'XRT_0_AutoML_20181120_154205': 0.006042541276377857}</pre>
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	<div class=" highlight hl-ipython3"><pre><span></span><span class="o">%</span><span class="k">matplotlib</span> inline
	<span class="n">metalearner</span><span class="o">.</span><span class="n">std_coef_plot</span><span class="p">()</span>
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	<pre>/Users/bear/anaconda/lib/python3.6/site-packages/matplotlib/cbook/deprecation.py:107: MatplotlibDeprecationWarning: Passing one of 'on', 'true', 'off', 'false' as a boolean is deprecated; use an actual boolean (True/False) instead.
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	GsKigyRJkiRJaoj/D3tJt1UkfPCrAAAAAElFTkSuQmCC
	"
	>
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	<p><strong>Getting a model directly by name</strong></p>

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	<div class="prompt input_prompt">In [87]:</div>
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	<div class=" highlight hl-ipython3"><pre><span></span><span class="n">aml_leaderboard_df</span><span class="o">.</span><span class="n">head</span><span class="p">()</span>
	</pre></div>

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	<div class="prompt output_prompt">Out[87]:</div>


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	<style>
	.dataframe thead tr:only-child th {
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	.dataframe tbody tr th {
	vertical-align: top;
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	<table border="1" class="dataframe">
	<thead>
	<tr style="text-align: right;">
	<th></th>
	<th>model_id</th>
	<th>auc</th>
	<th>logloss</th>
	<th>mean_per_class_error</th>
	<th>rmse</th>
	<th>mse</th>
	</tr>
	</thead>
	<tbody>
	<tr>
	<th>0</th>
	<td>StackedEnsemble_AllModels_0_AutoML_20181120_15...</td>
	<td>0.707120</td>
	<td>0.435531</td>
	<td>0.349509</td>
	<td>0.370103</td>
	<td>0.136977</td>
	</tr>
	<tr>
	<th>1</th>
	<td>StackedEnsemble_AllModels_0_AutoML_20181120_15...</td>
	<td>0.706222</td>
	<td>0.435883</td>
	<td>0.351685</td>
	<td>0.370262</td>
	<td>0.137094</td>
	</tr>
	<tr>
	<th>2</th>
	<td>StackedEnsemble_BestOfFamily_0_AutoML_20181120...</td>
	<td>0.705212</td>
	<td>0.436220</td>
	<td>0.350829</td>
	<td>0.370407</td>
	<td>0.137202</td>
	</tr>
	<tr>
	<th>3</th>
	<td>GBM_grid_0_AutoML_20181120_154205_model_0</td>
	<td>0.703839</td>
	<td>0.435055</td>
	<td>0.353507</td>
	<td>0.370225</td>
	<td>0.137067</td>
	</tr>
	<tr>
	<th>4</th>
	<td>GBM_grid_0_AutoML_20181120_153506_model_0</td>
	<td>0.703216</td>
	<td>0.435227</td>
	<td>0.352786</td>
	<td>0.370273</td>
	<td>0.137102</td>
	</tr>
	</tbody>
	</table>
	</div>
	</div>

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	<div class="cell border-box-sizing code_cell rendered">
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	<div class="prompt input_prompt">In [88]:</div>
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	<div class=" highlight hl-ipython3"><pre><span></span><span class="n">m_id</span><span class="o">=</span><span class="s1">''</span>
	<span class="k">for</span> <span class="n">model</span> <span class="ow">in</span> <span class="n">aml_leaderboard_df</span><span class="p">[</span><span class="s1">'model_id'</span><span class="p">]:</span>
	<span class="k">if</span> <span class="s1">'StackedEnsemble'</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">model</span><span class="p">:</span>
	<span class="nb">print</span> <span class="p">(</span><span class="n">model</span><span class="p">)</span>
	<span class="k">if</span> <span class="n">m_id</span><span class="o">==</span><span class="s1">''</span><span class="p">:</span>
	<span class="n">m_id</span><span class="o">=</span><span class="n">model</span>
	<span class="nb">print</span> <span class="p">(</span><span class="s2">"model_id "</span><span class="p">,</span> <span class="n">m_id</span><span class="p">)</span>
	</pre></div>

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	<pre>GBM_grid_0_AutoML_20181120_154205_model_0
	GBM_grid_0_AutoML_20181120_153506_model_0
	GBM_grid_0_AutoML_20181120_153506_model_1
	GBM_grid_0_AutoML_20181120_154205_model_1
	GBM_grid_0_AutoML_20181120_153506_model_2
	GBM_grid_0_AutoML_20181120_154205_model_2
	DeepLearning_0_AutoML_20181120_154205
	GLM_grid_0_AutoML_20181120_154205_model_0
	GLM_grid_0_AutoML_20181120_153506_model_0
	DeepLearning_0_AutoML_20181120_153506
	GBM_grid_0_AutoML_20181120_154205_model_4
	GBM_grid_0_AutoML_20181120_153506_model_4
	GBM_grid_0_AutoML_20181120_153506_model_3
	GBM_grid_0_AutoML_20181120_154205_model_3
	XRT_0_AutoML_20181120_154205
	XRT_0_AutoML_20181120_153506
	DRF_0_AutoML_20181120_154205
	DRF_0_AutoML_20181120_153506
	DRF_0_AutoML_20181120_153207
	model_id GBM_grid_0_AutoML_20181120_154205_model_0
	</pre>
	</div>
	</div>

	</div>
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	<div class="cell border-box-sizing code_cell rendered">
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	<div class="prompt input_prompt">In [89]:</div>
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	<div class=" highlight hl-ipython3"><pre><span></span><span class="n">non_stacked</span><span class="o">=</span> <span class="n">h2o</span><span class="o">.</span><span class="n">get_model</span><span class="p">(</span><span class="n">m_id</span><span class="p">)</span>
	<span class="nb">print</span> <span class="p">(</span><span class="n">non_stacked</span><span class="o">.</span><span class="n">algo</span><span class="p">)</span>
	</pre></div>

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	<pre>gbm
	</pre>
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	<div class="prompt input_prompt">In [90]:</div>
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	<div class=" highlight hl-ipython3"><pre><span></span><span class="nb">dir</span><span class="p">(</span><span class="n">non_stacked</span><span class="p">)</span>
	</pre></div>

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	<pre>['F0point5',
	'F1',
	'F2',
	'__class__',
	'__delattr__',
	'__dict__',
	'__dir__',
	'__doc__',
	'__eq__',
	'__format__',
	'__ge__',
	'__getattr__',
	'__getattribute__',
	'__gt__',
	'__hash__',
	'__init__',
	'__init_subclass__',
	'__le__',
	'__lt__',
	'__module__',
	'__ne__',
	'__new__',
	'__reduce__',
	'__reduce_ex__',
	'__repr__',
	'__setattr__',
	'__sizeof__',
	'__str__',
	'__subclasshook__',
	'__weakref__',
	'_bc',
	'_bcin',
	'_check_targets',
	'_compute_algo',
	'_estimator_type',
	'_future',
	'_get_metrics',
	'_have_mojo',
	'_have_pojo',
	'_id',
	'_is_xvalidated',
	'_job',
	'_keyify_if_h2oframe',
	'_metrics_class',
	'_model_json',
	'_parms',
	'_plot',
	'_requires_training_frame',
	'_resolve_model',
	'_verify_training_frame_params',
	'_xval_keys',
	'accuracy',
	'actual_params',
	'aic',
	'algo',
	'auc',
	'balance_classes',
	'biases',
	'build_tree_one_node',
	'calibrate_model',
	'calibration_frame',
	'categorical_encoding',
	'catoffsets',
	'checkpoint',
	'class_sampling_factors',
	'coef',
	'coef_norm',
	'col_sample_rate',
	'col_sample_rate_change_per_level',
	'col_sample_rate_per_tree',
	'confusion_matrix',
	'cross_validation_fold_assignment',
	'cross_validation_holdout_predictions',
	'cross_validation_metrics_summary',
	'cross_validation_models',
	'cross_validation_predictions',
	'custom_metric_func',
	'deepfeatures',
	'default_params',
	'distribution',
	'download_mojo',
	'download_pojo',
	'error',
	'fallout',
	'find_idx_by_threshold',
	'find_threshold_by_max_metric',
	'fit',
	'fnr',
	'fold_assignment',
	'fold_column',
	'fpr',
	'full_parameters',
	'gains_lift',
	'get_params',
	'get_xval_models',
	'gini',
	'have_mojo',
	'have_pojo',
	'histogram_type',
	'huber_alpha',
	'ignore_const_cols',
	'ignored_columns',
	'is_cross_validated',
	'join',
	'keep_cross_validation_fold_assignment',
	'keep_cross_validation_predictions',
	'learn_rate',
	'learn_rate_annealing',
	'levelone_frame_id',
	'logloss',
	'mae',
	'max_abs_leafnode_pred',
	'max_after_balance_size',
	'max_confusion_matrix_size',
	'max_depth',
	'max_hit_ratio_k',
	'max_per_class_error',
	'max_runtime_secs',
	'mcc',
	'mean_per_class_error',
	'mean_residual_deviance',
	'metalearner',
	'metric',
	'min_rows',
	'min_split_improvement',
	'missrate',
	'mixin',
	'model_id',
	'model_performance',
	'mse',
	'nbins',
	'nbins_cats',
	'nbins_top_level',
	'nfolds',
	'normmul',
	'normsub',
	'ntrees',
	'null_degrees_of_freedom',
	'null_deviance',
	'offset_column',
	'params',
	'parms',
	'partial_plot',
	'plot',
	'pprint_coef',
	'precision',
	'pred_noise_bandwidth',
	'predict',
	'predict_leaf_node_assignment',
	'quantile_alpha',
	'r2',
	'r2_stopping',
	'recall',
	'residual_degrees_of_freedom',
	'residual_deviance',
	'respmul',
	'response_column',
	'respsub',
	'rmse',
	'rmsle',
	'roc',
	'rotation',
	'sample_rate',
	'sample_rate_per_class',
	'save_model_details',
	'save_mojo',
	'score_each_iteration',
	'score_history',
	'score_tree_interval',
	'scoring_history',
	'seed',
	'sensitivity',
	'set_params',
	'show',
	'specificity',
	'start',
	'std_coef_plot',
	'stopping_metric',
	'stopping_rounds',
	'stopping_tolerance',
	'summary',
	'tnr',
	'tpr',
	'train',
	'training_frame',
	'tweedie_power',
	'type',
	'validation_frame',
	'varimp',
	'varimp_plot',
	'weights',
	'weights_column',
	'xval_keys',
	'xvals']</pre>
	</div>

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	<p>Note that since this is a pandas dataframe the data can be saved.</p>
	<p>The type of exploration depends on the learner. If the learner isn't an ensemble then ensemble exploration doesn't make sense.</p>

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	<p>Examine the variable importance of the metalearner (combiner) algorithm in the ensemble. This shows us how much each base learner is contributing to the ensemble. The AutoML Stacked Ensembles use the default metalearner algorithm (GLM with non-negative weights), so the variable importance of the metalearner is actually the standardized coefficient magnitudes of the GLM.</p>

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	<h2 id="Save-Leader-Model">Save Leader Model<a class="anchor-link" href="#Save-Leader-Model">¶</a></h2><p>There are two ways to save the leader model -- binary format and MOJO format. If you're taking your leader model to production, then we'd suggest the MOJO format since it's optimized for production use.</p>

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	<div class="cell border-box-sizing code_cell rendered">
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	<div class="prompt input_prompt">In [91]:</div>
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	<div class=" highlight hl-ipython3"><pre><span></span><span class="n">h2o</span><span class="o">.</span><span class="n">save_model</span><span class="p">(</span><span class="n">aml</span><span class="o">.</span><span class="n">leader</span><span class="p">,</span> <span class="n">path</span> <span class="o">=</span> <span class="s2">"./models"</span><span class="p">)</span>
	</pre></div>

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	<pre>'/Users/bear/Documents/INFO_7390/H2O/models/StackedEnsemble_AllModels_0_AutoML_20181120_154205'</pre>
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	<div class="cell border-box-sizing code_cell rendered">
	<div class="input">
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	<div class="inner_cell">
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	<div class=" highlight hl-ipython3"><pre><span></span><span class="n">aml</span><span class="o">.</span><span class="n">leader</span><span class="o">.</span><span class="n">download_mojo</span><span class="p">(</span><span class="n">path</span> <span class="o">=</span> <span class="s2">"./models"</span><span class="p">)</span>
	</pre></div>

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	<pre>'/Users/bear/Documents/INFO_7390/H2O/models/StackedEnsemble_AllModels_0_AutoML_20181120_154205.zip'</pre>
	</div>

	</div>

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	<h2 id="Making-predictions">Making predictions<a class="anchor-link" href="#Making-predictions">¶</a></h2><p>If one wants predictions the user will do this on new data.</p>
	<p>Here we are taking 10% of original file just to show the syntax</p>

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	<div class="cell border-box-sizing code_cell rendered">
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	<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># split into training and test for showing how to predict</span>
	<span class="n">train</span><span class="p">,</span> <span class="n">test</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">split_frame</span><span class="p">([</span><span class="mf">0.8</span><span class="p">])</span>
	</pre></div>

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	<h2 id="Predict-Using-Leader-Model">Predict Using Leader Model<a class="anchor-link" href="#Predict-Using-Leader-Model">¶</a></h2><p>If you need to generate predictions on a test set, you can make predictions on the <code>"H2OAutoML"</code> object directly, or on the leader model object.</p>

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	<div class=" highlight hl-ipython3"><pre><span></span><span class="n">pred</span> <span class="o">=</span> <span class="n">aml</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">test</span><span class="p">)</span>
	<span class="n">pred</span><span class="o">.</span><span class="n">head</span><span class="p">()</span>
	</pre></div>

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	<pre>stackedensemble prediction progress: \|████████████████████████████████████\| 100%
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	<thead>
	<tr><th style="text-align: right;"> predict</th><th style="text-align: right;"> p0</th><th style="text-align: right;"> p1</th></tr>
	</thead>
	<tbody>
	<tr><td style="text-align: right;"> 1</td><td style="text-align: right;">0.709939</td><td style="text-align: right;">0.290061 </td></tr>
	<tr><td style="text-align: right;"> 1</td><td style="text-align: right;">0.645258</td><td style="text-align: right;">0.354742 </td></tr>
	<tr><td style="text-align: right;"> 1</td><td style="text-align: right;">0.701456</td><td style="text-align: right;">0.298544 </td></tr>
	<tr><td style="text-align: right;"> 0</td><td style="text-align: right;">0.865275</td><td style="text-align: right;">0.134725 </td></tr>
	<tr><td style="text-align: right;"> 0</td><td style="text-align: right;">0.899026</td><td style="text-align: right;">0.100974 </td></tr>
	<tr><td style="text-align: right;"> 0</td><td style="text-align: right;">0.865134</td><td style="text-align: right;">0.134866 </td></tr>
	<tr><td style="text-align: right;"> 1</td><td style="text-align: right;">0.624003</td><td style="text-align: right;">0.375997 </td></tr>
	<tr><td style="text-align: right;"> 0</td><td style="text-align: right;">0.921187</td><td style="text-align: right;">0.0788131</td></tr>
	<tr><td style="text-align: right;"> 0</td><td style="text-align: right;">0.903194</td><td style="text-align: right;">0.0968065</td></tr>
	<tr><td style="text-align: right;"> 0</td><td style="text-align: right;">0.925731</td><td style="text-align: right;">0.0742695</td></tr>
	</tbody>
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	<pre></pre>
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	<h2 id="model_performance()">model_performance()<a class="anchor-link" href="#model_performance()">¶</a></h2><p>The standard <code>model_performance()</code> method can be applied to the AutoML leader model and a test set to generate an H2O model performance object.</p>

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	<div class=" highlight hl-ipython3"><pre><span></span><span class="n">perf</span> <span class="o">=</span> <span class="n">aml</span><span class="o">.</span><span class="n">leader</span><span class="o">.</span><span class="n">model_performance</span><span class="p">(</span><span class="n">test</span><span class="p">)</span>
	<span class="n">perf</span>
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	<pre>
	ModelMetricsBinomialGLM: stackedensemble
	Reported on test data.

	MSE: 0.13055715415749164
	RMSE: 0.36132693527813786
	LogLoss: 0.41655140391705325
	Null degrees of freedom: 32682
	Residual degrees of freedom: 32671
	Null deviance: 31504.82333185961
	Residual deviance: 27228.299068442102
	AIC: 27252.299068442102
	AUC: 0.764167884838059
	Gini: 0.528335769676118
	Confusion Matrix (Act/Pred) for max f1 @ threshold = 0.21295302564978025:
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	<div style="overflow:auto"><table style="width:50%"><tr><td><b></b></td>
	<td><b>0</b></td>
	<td><b>1</b></td>
	<td><b>Error</b></td>
	<td><b>Rate</b></td></tr>
	<tr><td>0</td>
	<td>20323.0</td>
	<td>6247.0</td>
	<td>0.2351</td>
	<td> (6247.0/26570.0)</td></tr>
	<tr><td>1</td>
	<td>2383.0</td>
	<td>3730.0</td>
	<td>0.3898</td>
	<td> (2383.0/6113.0)</td></tr>
	<tr><td>Total</td>
	<td>22706.0</td>
	<td>9977.0</td>
	<td>0.2641</td>
	<td> (8630.0/32683.0)</td></tr></table></div>
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	<pre>Maximum Metrics: Maximum metrics at their respective thresholds

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	<div style="overflow:auto"><table style="width:50%"><tr><td><b>metric</b></td>
	<td><b>threshold</b></td>
	<td><b>value</b></td>
	<td><b>idx</b></td></tr>
	<tr><td>max f1</td>
	<td>0.2129530</td>
	<td>0.4636420</td>
	<td>234.0</td></tr>
	<tr><td>max f2</td>
	<td>0.1407219</td>
	<td>0.6066398</td>
	<td>306.0</td></tr>
	<tr><td>max f0point5</td>
	<td>0.3219515</td>
	<td>0.4539944</td>
	<td>156.0</td></tr>
	<tr><td>max accuracy</td>
	<td>0.4260168</td>
	<td>0.8235168</td>
	<td>99.0</td></tr>
	<tr><td>max precision</td>
	<td>0.6726948</td>
	<td>0.8888889</td>
	<td>9.0</td></tr>
	<tr><td>max recall</td>
	<td>0.0679730</td>
	<td>1.0</td>
	<td>393.0</td></tr>
	<tr><td>max specificity</td>
	<td>0.7559667</td>
	<td>0.9999624</td>
	<td>0.0</td></tr>
	<tr><td>max absolute_mcc</td>
	<td>0.2294254</td>
	<td>0.3180632</td>
	<td>221.0</td></tr>
	<tr><td>max min_per_class_accuracy</td>
	<td>0.1851642</td>
	<td>0.6908228</td>
	<td>260.0</td></tr>
	<tr><td>max mean_per_class_accuracy</td>
	<td>0.1802490</td>
	<td>0.6935079</td>
	<td>265.0</td></tr></table></div>
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	<pre>Gains/Lift Table: Avg response rate: 18.70 %

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	<div style="overflow:auto"><table style="width:50%"><tr><td><b></b></td>
	<td><b>group</b></td>
	<td><b>cumulative_data_fraction</b></td>
	<td><b>lower_threshold</b></td>
	<td><b>lift</b></td>
	<td><b>cumulative_lift</b></td>
	<td><b>response_rate</b></td>
	<td><b>cumulative_response_rate</b></td>
	<td><b>capture_rate</b></td>
	<td><b>cumulative_capture_rate</b></td>
	<td><b>gain</b></td>
	<td><b>cumulative_gain</b></td></tr>
	<tr><td></td>
	<td>1</td>
	<td>0.0100052</td>
	<td>0.5792591</td>
	<td>3.9240181</td>
	<td>3.9240181</td>
	<td>0.7339450</td>
	<td>0.7339450</td>
	<td>0.0392606</td>
	<td>0.0392606</td>
	<td>292.4018148</td>
	<td>292.4018148</td></tr>
	<tr><td></td>
	<td>2</td>
	<td>0.0200104</td>
	<td>0.5330392</td>
	<td>3.3681156</td>
	<td>3.6460669</td>
	<td>0.6299694</td>
	<td>0.6819572</td>
	<td>0.0336987</td>
	<td>0.0729593</td>
	<td>236.8115577</td>
	<td>264.6066862</td></tr>
	<tr><td></td>
	<td>3</td>
	<td>0.0300156</td>
	<td>0.4993342</td>
	<td>3.0738142</td>
	<td>3.4553160</td>
	<td>0.5749235</td>
	<td>0.6462793</td>
	<td>0.0307541</td>
	<td>0.1037134</td>
	<td>207.3814216</td>
	<td>245.5315980</td></tr>
	<tr><td></td>
	<td>4</td>
	<td>0.0400208</td>
	<td>0.4721518</td>
	<td>2.6977625</td>
	<td>3.2659276</td>
	<td>0.5045872</td>
	<td>0.6108563</td>
	<td>0.0269917</td>
	<td>0.1307051</td>
	<td>169.7762476</td>
	<td>226.5927604</td></tr>
	<tr><td></td>
	<td>5</td>
	<td>0.0500260</td>
	<td>0.4484122</td>
	<td>2.9430136</td>
	<td>3.2013448</td>
	<td>0.5504587</td>
	<td>0.5987768</td>
	<td>0.0294454</td>
	<td>0.1601505</td>
	<td>194.3013611</td>
	<td>220.1344805</td></tr>
	<tr><td></td>
	<td>6</td>
	<td>0.1000214</td>
	<td>0.3612914</td>
	<td>2.3820279</td>
	<td>2.7918117</td>
	<td>0.4455324</td>
	<td>0.5221780</td>
	<td>0.1190905</td>
	<td>0.2792410</td>
	<td>138.2027907</td>
	<td>179.1811672</td></tr>
	<tr><td></td>
	<td>7</td>
	<td>0.1500168</td>
	<td>0.3076471</td>
	<td>1.9992020</td>
	<td>2.5276623</td>
	<td>0.3739290</td>
	<td>0.4727718</td>
	<td>0.0999509</td>
	<td>0.3791919</td>
	<td>99.9201994</td>
	<td>152.7662332</td></tr>
	<tr><td></td>
	<td>8</td>
	<td>0.2000122</td>
	<td>0.2681940</td>
	<td>1.7145366</td>
	<td>2.3244120</td>
	<td>0.3206854</td>
	<td>0.4347560</td>
	<td>0.0857190</td>
	<td>0.4649108</td>
	<td>71.4536571</td>
	<td>132.4411989</td></tr>
	<tr><td></td>
	<td>9</td>
	<td>0.3000031</td>
	<td>0.2147773</td>
	<td>1.3873349</td>
	<td>2.0120848</td>
	<td>0.2594859</td>
	<td>0.3763386</td>
	<td>0.1387208</td>
	<td>0.6036316</td>
	<td>38.7334935</td>
	<td>101.2084828</td></tr>
	<tr><td></td>
	<td>10</td>
	<td>0.3999939</td>
	<td>0.1779800</td>
	<td>1.0993975</td>
	<td>1.7839304</td>
	<td>0.2056304</td>
	<td>0.3336648</td>
	<td>0.1099297</td>
	<td>0.7135613</td>
	<td>9.9397496</td>
	<td>78.3930449</td></tr>
	<tr><td></td>
	<td>11</td>
	<td>0.5000153</td>
	<td>0.1507619</td>
	<td>0.8880807</td>
	<td>1.6047276</td>
	<td>0.1661058</td>
	<td>0.3001469</td>
	<td>0.0888271</td>
	<td>0.8023884</td>
	<td>-11.1919310</td>
	<td>60.4727606</td></tr>
	<tr><td></td>
	<td>12</td>
	<td>0.6000061</td>
	<td>0.1301321</td>
	<td>0.6854874</td>
	<td>1.4515365</td>
	<td>0.1282130</td>
	<td>0.2714941</td>
	<td>0.0685425</td>
	<td>0.8709308</td>
	<td>-31.4512573</td>
	<td>45.1536534</td></tr>
	<tr><td></td>
	<td>13</td>
	<td>0.6999969</td>
	<td>0.1126705</td>
	<td>0.5137066</td>
	<td>1.3175725</td>
	<td>0.0960832</td>
	<td>0.2464376</td>
	<td>0.0513659</td>
	<td>0.9222967</td>
	<td>-48.6293432</td>
	<td>31.7572537</td></tr>
	<tr><td></td>
	<td>14</td>
	<td>0.7999878</td>
	<td>0.0979212</td>
	<td>0.4466302</td>
	<td>1.2087131</td>
	<td>0.0835373</td>
	<td>0.2260766</td>
	<td>0.0446589</td>
	<td>0.9669557</td>
	<td>-55.3369767</td>
	<td>20.8713077</td></tr>
	<tr><td></td>
	<td>15</td>
	<td>0.8999786</td>
	<td>0.0825174</td>
	<td>0.2486732</td>
	<td>1.1020492</td>
	<td>0.0465116</td>
	<td>0.2061263</td>
	<td>0.0248650</td>
	<td>0.9918207</td>
	<td>-75.1326757</td>
	<td>10.2049237</td></tr>
	<tr><td></td>
	<td>16</td>
	<td>1.0</td>
	<td>0.0605814</td>
	<td>0.0817754</td>
	<td>1.0</td>
	<td>0.0152952</td>
	<td>0.1870391</td>
	<td>0.0081793</td>
	<td>1.0</td>
	<td>-91.8224614</td>
	<td>0.0</td></tr></table></div>
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	<pre></pre>
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	<div class="cell border-box-sizing code_cell rendered">
	<div class="input">
	<div class="prompt input_prompt">In [96]:</div>
	<div class="inner_cell">
	<div class="input_area">
	<div class=" highlight hl-ipython3"><pre><span></span><span class="nb">dir</span><span class="p">(</span><span class="n">perf</span><span class="p">)</span>
	</pre></div>

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	<pre>['F0point5',
	'F1',
	'F2',
	'__class__',
	'__delattr__',
	'__dict__',
	'__dir__',
	'__doc__',
	'__eq__',
	'__format__',
	'__ge__',
	'__getattr__',
	'__getattribute__',
	'__getitem__',
	'__gt__',
	'__hash__',
	'__init__',
	'__init_subclass__',
	'__le__',
	'__lt__',
	'__module__',
	'__ne__',
	'__new__',
	'__reduce__',
	'__reduce_ex__',
	'__repr__',
	'__setattr__',
	'__sizeof__',
	'__str__',
	'__subclasshook__',
	'__weakref__',
	'_algo',
	'_bc',
	'_bcin',
	'_has',
	'_metric_json',
	'_on_train',
	'_on_valid',
	'_on_xval',
	'accuracy',
	'aic',
	'auc',
	'confusion_matrix',
	'custom_metric_name',
	'custom_metric_value',
	'error',
	'fallout',
	'find_idx_by_threshold',
	'find_threshold_by_max_metric',
	'fnr',
	'fpr',
	'fprs',
	'gains_lift',
	'gini',
	'logloss',
	'mae',
	'make',
	'max_per_class_error',
	'mcc',
	'mean_per_class_error',
	'mean_residual_deviance',
	'metric',
	'missrate',
	'mse',
	'nobs',
	'null_degrees_of_freedom',
	'null_deviance',
	'plot',
	'precision',
	'r2',
	'recall',
	'residual_degrees_of_freedom',
	'residual_deviance',
	'rmse',
	'rmsle',
	'sensitivity',
	'show',
	'specificity',
	'tnr',
	'tpr',
	'tprs']</pre>
	</div>

	</div>

	</div>
	</div>

	</div>
	<div class="cell border-box-sizing code_cell rendered">
	<div class="input">
	<div class="prompt input_prompt">In [97]:</div>
	<div class="inner_cell">
	<div class="input_area">
	<div class=" highlight hl-ipython3"><pre><span></span><span class="n">d</span><span class="o">=</span><span class="n">perf</span><span class="o">.</span><span class="n">confusion_matrix</span><span class="p">()</span>
	<span class="n">d</span>
	</pre></div>

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	<pre>Confusion Matrix (Act/Pred) for max f1 @ threshold = 0.21295302564978025:
	</pre>
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	<div class="output_html rendered_html output_subarea ">
	<div style="overflow:auto"><table style="width:50%"><tr><td><b></b></td>
	<td><b>0</b></td>
	<td><b>1</b></td>
	<td><b>Error</b></td>
	<td><b>Rate</b></td></tr>
	<tr><td>0</td>
	<td>20323.0</td>
	<td>6247.0</td>
	<td>0.2351</td>
	<td> (6247.0/26570.0)</td></tr>
	<tr><td>1</td>
	<td>2383.0</td>
	<td>3730.0</td>
	<td>0.3898</td>
	<td> (2383.0/6113.0)</td></tr>
	<tr><td>Total</td>
	<td>22706.0</td>
	<td>9977.0</td>
	<td>0.2641</td>
	<td> (8630.0/32683.0)</td></tr></table></div>
	</div>

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	<pre></pre>
	</div>

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	</div>

	</div>
	<div class="cell border-box-sizing code_cell rendered">
	<div class="input">
	<div class="prompt input_prompt">In [98]:</div>
	<div class="inner_cell">
	<div class="input_area">
	<div class=" highlight hl-ipython3"><pre><span></span><span class="nb">dir</span><span class="p">(</span><span class="n">perf</span><span class="p">)</span>
	</pre></div>

	</div>
	</div>
	</div>

	<div class="output_wrapper">
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	<pre>['F0point5',
	'F1',
	'F2',
	'__class__',
	'__delattr__',
	'__dict__',
	'__dir__',
	'__doc__',
	'__eq__',
	'__format__',
	'__ge__',
	'__getattr__',
	'__getattribute__',
	'__getitem__',
	'__gt__',
	'__hash__',
	'__init__',
	'__init_subclass__',
	'__le__',
	'__lt__',
	'__module__',
	'__ne__',
	'__new__',
	'__reduce__',
	'__reduce_ex__',
	'__repr__',
	'__setattr__',
	'__sizeof__',
	'__str__',
	'__subclasshook__',
	'__weakref__',
	'_algo',
	'_bc',
	'_bcin',
	'_has',
	'_metric_json',
	'_on_train',
	'_on_valid',
	'_on_xval',
	'accuracy',
	'aic',
	'auc',
	'confusion_matrix',
	'custom_metric_name',
	'custom_metric_value',
	'error',
	'fallout',
	'find_idx_by_threshold',
	'find_threshold_by_max_metric',
	'fnr',
	'fpr',
	'fprs',
	'gains_lift',
	'gini',
	'logloss',
	'mae',
	'make',
	'max_per_class_error',
	'mcc',
	'mean_per_class_error',
	'mean_residual_deviance',
	'metric',
	'missrate',
	'mse',
	'nobs',
	'null_degrees_of_freedom',
	'null_deviance',
	'plot',
	'precision',
	'r2',
	'recall',
	'residual_degrees_of_freedom',
	'residual_deviance',
	'rmse',
	'rmsle',
	'sensitivity',
	'show',
	'specificity',
	'tnr',
	'tpr',
	'tprs']</pre>
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	<p>In R we get plots like:</p>

	<pre><code>#compute performance
	</code></pre>
	<p>perf <- h2o.performance(automl_leader,conv_data.hex)
	h2o.confusionMatrix(perf)
	h2o.accuracy(perf)
	h2o.tpr(perf)</p>

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	<div class=" highlight hl-ipython3"><pre><span></span><span class="n">aml</span><span class="o">.</span><span class="n">leader</span><span class="o">.</span><span class="n">algo</span>
	</pre></div>

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	<pre>'stackedensemble'</pre>
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	<div class=" highlight hl-ipython3"><pre><span></span><span class="nb">dir</span><span class="p">(</span><span class="n">aml</span><span class="o">.</span><span class="n">leader</span><span class="p">)</span>
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	<pre>['F0point5',
	'F1',
	'F2',
	'__class__',
	'__delattr__',
	'__dict__',
	'__dir__',
	'__doc__',
	'__eq__',
	'__format__',
	'__ge__',
	'__getattr__',
	'__getattribute__',
	'__gt__',
	'__hash__',
	'__init__',
	'__init_subclass__',
	'__le__',
	'__lt__',
	'__module__',
	'__ne__',
	'__new__',
	'__reduce__',
	'__reduce_ex__',
	'__repr__',
	'__setattr__',
	'__sizeof__',
	'__str__',
	'__subclasshook__',
	'__weakref__',
	'_bc',
	'_bcin',
	'_check_targets',
	'_compute_algo',
	'_estimator_type',
	'_future',
	'_get_metrics',
	'_have_mojo',
	'_have_pojo',
	'_id',
	'_is_xvalidated',
	'_job',
	'_keyify_if_h2oframe',
	'_metrics_class',
	'_model_json',
	'_parms',
	'_plot',
	'_requires_training_frame',
	'_resolve_model',
	'_verify_training_frame_params',
	'_xval_keys',
	'accuracy',
	'actual_params',
	'aic',
	'algo',
	'auc',
	'base_models',
	'biases',
	'catoffsets',
	'coef',
	'coef_norm',
	'confusion_matrix',
	'cross_validation_fold_assignment',
	'cross_validation_holdout_predictions',
	'cross_validation_metrics_summary',
	'cross_validation_models',
	'cross_validation_predictions',
	'deepfeatures',
	'default_params',
	'download_mojo',
	'download_pojo',
	'error',
	'fallout',
	'find_idx_by_threshold',
	'find_threshold_by_max_metric',
	'fit',
	'fnr',
	'fpr',
	'full_parameters',
	'gains_lift',
	'get_params',
	'get_xval_models',
	'gini',
	'have_mojo',
	'have_pojo',
	'is_cross_validated',
	'join',
	'keep_levelone_frame',
	'levelone_frame_id',
	'logloss',
	'mae',
	'max_per_class_error',
	'mcc',
	'mean_per_class_error',
	'mean_residual_deviance',
	'metalearner',
	'metalearner_algorithm',
	'metalearner_fold_assignment',
	'metalearner_fold_column',
	'metalearner_nfolds',
	'metalearner_params',
	'metric',
	'missrate',
	'mixin',
	'model_id',
	'model_performance',
	'mse',
	'normmul',
	'normsub',
	'null_degrees_of_freedom',
	'null_deviance',
	'params',
	'parms',
	'partial_plot',
	'plot',
	'pprint_coef',
	'precision',
	'predict',
	'predict_leaf_node_assignment',
	'r2',
	'recall',
	'residual_degrees_of_freedom',
	'residual_deviance',
	'respmul',
	'response_column',
	'respsub',
	'rmse',
	'rmsle',
	'roc',
	'rotation',
	'save_model_details',
	'save_mojo',
	'score_history',
	'scoring_history',
	'seed',
	'sensitivity',
	'set_params',
	'show',
	'specificity',
	'start',
	'std_coef_plot',
	'summary',
	'tnr',
	'tpr',
	'train',
	'training_frame',
	'type',
	'validation_frame',
	'varimp',
	'varimp_plot',
	'weights',
	'xval_keys',
	'xvals']</pre>
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	<div class=" highlight hl-ipython3"><pre><span></span><span class="n">aml</span><span class="o">.</span><span class="n">leader</span><span class="o">.</span><span class="n">model_performance</span><span class="p">(</span><span class="n">test</span><span class="p">)</span><span class="o">.</span><span class="n">auc</span><span class="p">()</span>
	</pre></div>

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	<pre>0.764167884838059</pre>
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	<div class=" highlight hl-ipython3"><pre><span></span><span class="n">best_perf</span> <span class="o">=</span> <span class="n">aml</span><span class="o">.</span><span class="n">leader</span><span class="o">.</span><span class="n">model_performance</span><span class="p">()</span>
	<span class="n">best_perf</span>
	</pre></div>

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	<pre>
	ModelMetricsBinomialGLM: stackedensemble
	Reported on train data.

	MSE: 0.12685990330985406
	RMSE: 0.3561739789904002
	LogLoss: 0.40703958453227496
	Null degrees of freedom: 130954
	Residual degrees of freedom: 130943
	Null deviance: 124374.13927893189
	Residual deviance: 106607.73758484815
	AIC: 106631.73758484815
	AUC: 0.7734040182726795
	Gini: 0.5468080365453589
	Confusion Matrix (Act/Pred) for max f1 @ threshold = 0.21708051286464972:
	</pre>
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	<div style="overflow:auto"><table style="width:50%"><tr><td><b></b></td>
	<td><b>0</b></td>
	<td><b>1</b></td>
	<td><b>Error</b></td>
	<td><b>Rate</b></td></tr>
	<tr><td>0</td>
	<td>83212.0</td>
	<td>23869.0</td>
	<td>0.2229</td>
	<td> (23869.0/107081.0)</td></tr>
	<tr><td>1</td>
	<td>9376.0</td>
	<td>14498.0</td>
	<td>0.3927</td>
	<td> (9376.0/23874.0)</td></tr>
	<tr><td>Total</td>
	<td>92588.0</td>
	<td>38367.0</td>
	<td>0.2539</td>
	<td> (33245.0/130955.0)</td></tr></table></div>
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	<pre>Maximum Metrics: Maximum metrics at their respective thresholds

	</pre>
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	<div style="overflow:auto"><table style="width:50%"><tr><td><b>metric</b></td>
	<td><b>threshold</b></td>
	<td><b>value</b></td>
	<td><b>idx</b></td></tr>
	<tr><td>max f1</td>
	<td>0.2170805</td>
	<td>0.4658666</td>
	<td>238.0</td></tr>
	<tr><td>max f2</td>
	<td>0.1410190</td>
	<td>0.6067433</td>
	<td>309.0</td></tr>
	<tr><td>max f0point5</td>
	<td>0.3338429</td>
	<td>0.4568693</td>
	<td>155.0</td></tr>
	<tr><td>max accuracy</td>
	<td>0.4390853</td>
	<td>0.8290100</td>
	<td>98.0</td></tr>
	<tr><td>max precision</td>
	<td>0.8006766</td>
	<td>1.0</td>
	<td>0.0</td></tr>
	<tr><td>max recall</td>
	<td>0.0676438</td>
	<td>1.0</td>
	<td>394.0</td></tr>
	<tr><td>max specificity</td>
	<td>0.8006766</td>
	<td>1.0</td>
	<td>0.0</td></tr>
	<tr><td>max absolute_mcc</td>
	<td>0.2335835</td>
	<td>0.3269004</td>
	<td>224.0</td></tr>
	<tr><td>max min_per_class_accuracy</td>
	<td>0.1855661</td>
	<td>0.6993958</td>
	<td>265.0</td></tr>
	<tr><td>max mean_per_class_accuracy</td>
	<td>0.1761337</td>
	<td>0.7006208</td>
	<td>274.0</td></tr></table></div>
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	<pre>Gains/Lift Table: Avg response rate: 18.23 %

	</pre>
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	<div style="overflow:auto"><table style="width:50%"><tr><td><b></b></td>
	<td><b>group</b></td>
	<td><b>cumulative_data_fraction</b></td>
	<td><b>lower_threshold</b></td>
	<td><b>lift</b></td>
	<td><b>cumulative_lift</b></td>
	<td><b>response_rate</b></td>
	<td><b>cumulative_response_rate</b></td>
	<td><b>capture_rate</b></td>
	<td><b>cumulative_capture_rate</b></td>
	<td><b>gain</b></td>
	<td><b>cumulative_gain</b></td></tr>
	<tr><td></td>
	<td>1</td>
	<td>0.0100034</td>
	<td>0.5809896</td>
	<td>4.2290904</td>
	<td>4.2290904</td>
	<td>0.7709924</td>
	<td>0.7709924</td>
	<td>0.0423054</td>
	<td>0.0423054</td>
	<td>322.9090447</td>
	<td>322.9090447</td></tr>
	<tr><td></td>
	<td>2</td>
	<td>0.0200069</td>
	<td>0.5350310</td>
	<td>3.4879528</td>
	<td>3.8585216</td>
	<td>0.6358779</td>
	<td>0.7034351</td>
	<td>0.0348915</td>
	<td>0.0771970</td>
	<td>248.7952815</td>
	<td>285.8521631</td></tr>
	<tr><td></td>
	<td>3</td>
	<td>0.0300027</td>
	<td>0.5007744</td>
	<td>3.1972882</td>
	<td>3.6382227</td>
	<td>0.5828877</td>
	<td>0.6632731</td>
	<td>0.0319595</td>
	<td>0.1091564</td>
	<td>219.7288214</td>
	<td>263.8222689</td></tr>
	<tr><td></td>
	<td>4</td>
	<td>0.0400061</td>
	<td>0.4718430</td>
	<td>2.9436144</td>
	<td>3.4645375</td>
	<td>0.5366412</td>
	<td>0.6316091</td>
	<td>0.0294463</td>
	<td>0.1386027</td>
	<td>194.3614440</td>
	<td>246.4537481</td></tr>
	<tr><td></td>
	<td>5</td>
	<td>0.0500019</td>
	<td>0.4483865</td>
	<td>2.8704357</td>
	<td>3.3457716</td>
	<td>0.5233002</td>
	<td>0.6099572</td>
	<td>0.0286923</td>
	<td>0.1672950</td>
	<td>187.0435684</td>
	<td>234.5771560</td></tr>
	<tr><td></td>
	<td>6</td>
	<td>0.1000038</td>
	<td>0.3623038</td>
	<td>2.4444070</td>
	<td>2.8950893</td>
	<td>0.4456323</td>
	<td>0.5277947</td>
	<td>0.1222250</td>
	<td>0.2895200</td>
	<td>144.4406963</td>
	<td>189.5089261</td></tr>
	<tr><td></td>
	<td>7</td>
	<td>0.1500057</td>
	<td>0.3079302</td>
	<td>1.9878608</td>
	<td>2.5926798</td>
	<td>0.3624007</td>
	<td>0.4726634</td>
	<td>0.0993968</td>
	<td>0.3889168</td>
	<td>98.7860769</td>
	<td>159.2679764</td></tr>
	<tr><td></td>
	<td>8</td>
	<td>0.2</td>
	<td>0.2684456</td>
	<td>1.7116814</td>
	<td>2.3724554</td>
	<td>0.3120513</td>
	<td>0.4325150</td>
	<td>0.0855743</td>
	<td>0.4744911</td>
	<td>71.1681359</td>
	<td>137.2455391</td></tr>
	<tr><td></td>
	<td>9</td>
	<td>0.3000038</td>
	<td>0.2132009</td>
	<td>1.4102670</td>
	<td>2.0517178</td>
	<td>0.2571014</td>
	<td>0.3740423</td>
	<td>0.1410321</td>
	<td>0.6155232</td>
	<td>41.0267006</td>
	<td>105.1717765</td></tr>
	<tr><td></td>
	<td>10</td>
	<td>0.4</td>
	<td>0.1765625</td>
	<td>1.1217652</td>
	<td>1.8192385</td>
	<td>0.2045055</td>
	<td>0.3316597</td>
	<td>0.1121722</td>
	<td>0.7276954</td>
	<td>12.1765206</td>
	<td>81.9238502</td></tr>
	<tr><td></td>
	<td>11</td>
	<td>0.5000038</td>
	<td>0.1503145</td>
	<td>0.8745582</td>
	<td>1.6302967</td>
	<td>0.1594380</td>
	<td>0.2972143</td>
	<td>0.0874592</td>
	<td>0.8151546</td>
	<td>-12.5441786</td>
	<td>63.0296674</td></tr>
	<tr><td></td>
	<td>12</td>
	<td>0.6</td>
	<td>0.1300345</td>
	<td>0.6769128</td>
	<td>1.4714054</td>
	<td>0.1234059</td>
	<td>0.2682474</td>
	<td>0.0676887</td>
	<td>0.8828433</td>
	<td>-32.3087165</td>
	<td>47.1405434</td></tr>
	<tr><td></td>
	<td>13</td>
	<td>0.6999962</td>
	<td>0.1129563</td>
	<td>0.4959559</td>
	<td>1.3320601</td>
	<td>0.0904162</td>
	<td>0.2428437</td>
	<td>0.0495937</td>
	<td>0.9324370</td>
	<td>-50.4044061</td>
	<td>33.2060067</td></tr>
	<tr><td></td>
	<td>14</td>
	<td>0.8</td>
	<td>0.0978849</td>
	<td>0.3920433</td>
	<td>1.2145535</td>
	<td>0.0714722</td>
	<td>0.2214215</td>
	<td>0.0392058</td>
	<td>0.9716428</td>
	<td>-60.7956663</td>
	<td>21.4553489</td></tr>
	<tr><td></td>
	<td>15</td>
	<td>0.8999962</td>
	<td>0.0824531</td>
	<td>0.2194940</td>
	<td>1.1039951</td>
	<td>0.0400153</td>
	<td>0.2012659</td>
	<td>0.0219486</td>
	<td>0.9935914</td>
	<td>-78.0505987</td>
	<td>10.3995078</td></tr>
	<tr><td></td>
	<td>16</td>
	<td>1.0</td>
	<td>0.0597755</td>
	<td>0.0640840</td>
	<td>1.0</td>
	<td>0.0116830</td>
	<td>0.1823069</td>
	<td>0.0064086</td>
	<td>1.0</td>
	<td>-93.5915993</td>
	<td>0.0</td></tr></table></div>
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	<div class=" highlight hl-ipython3"><pre><span></span><span class="n">best_perf</span><span class="o">.</span><span class="n">plot</span><span class="p">()</span>
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	"
	>
	</div>

	</div>

	</div>
	</div>

	</div>
	<div class="cell border-box-sizing code_cell rendered">
	<div class="input">
	<div class="prompt input_prompt">In [104]:</div>
	<div class="inner_cell">
	<div class="input_area">
	<div class=" highlight hl-ipython3"><pre><span></span><span class="n">aml</span><span class="o">.</span><span class="n">leader</span><span class="o">.</span><span class="n">confusion_matrix</span><span class="p">()</span>
	</pre></div>

	</div>
	</div>
	</div>

	<div class="output_wrapper">
	<div class="output">


	<div class="output_area">
	<div class="prompt"></div>

	<div class="output_subarea output_stream output_stdout output_text">
	<pre>Confusion Matrix (Act/Pred) for max f1 @ threshold = 0.21708051286464972:
	</pre>
	</div>
	</div>

	<div class="output_area">
	<div class="prompt"></div>


	<div class="output_html rendered_html output_subarea ">
	<div style="overflow:auto"><table style="width:50%"><tr><td><b></b></td>
	<td><b>0</b></td>
	<td><b>1</b></td>
	<td><b>Error</b></td>
	<td><b>Rate</b></td></tr>
	<tr><td>0</td>
	<td>83212.0</td>
	<td>23869.0</td>
	<td>0.2229</td>
	<td> (23869.0/107081.0)</td></tr>
	<tr><td>1</td>
	<td>9376.0</td>
	<td>14498.0</td>
	<td>0.3927</td>
	<td> (9376.0/23874.0)</td></tr>
	<tr><td>Total</td>
	<td>92588.0</td>
	<td>38367.0</td>
	<td>0.2539</td>
	<td> (33245.0/130955.0)</td></tr></table></div>
	</div>

	</div>

	<div class="output_area">
	<div class="prompt output_prompt">Out[104]:</div>



	<div class="output_text output_subarea output_execute_result">
	<pre></pre>
	</div>

	</div>

	</div>
	</div>

	</div>
	<div class="cell border-box-sizing code_cell rendered">
	<div class="input">
	<div class="prompt input_prompt">In [105]:</div>
	<div class="inner_cell">
	<div class="input_area">
	<div class=" highlight hl-ipython3"><pre><span></span><span class="n">roc</span><span class="o">=</span><span class="n">aml</span><span class="o">.</span><span class="n">leader</span><span class="o">.</span><span class="n">roc</span><span class="p">()</span>
	<span class="n">roc</span>
	</pre></div>

	</div>
	</div>
	</div>

	<div class="output_wrapper">
	<div class="output">


	<div class="output_area">
	<div class="prompt output_prompt">Out[105]:</div>



	<div class="output_text output_subarea output_execute_result">
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	<div class="cell border-box-sizing code_cell rendered">
	<div class="input">
	<div class="prompt input_prompt">In [106]:</div>
	<div class="inner_cell">
	<div class="input_area">
	<div class=" highlight hl-ipython3"><pre><span></span><span class="n">aml</span><span class="o">.</span><span class="n">leader</span><span class="o">.</span><span class="n">tnr</span>
	</pre></div>

	</div>
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	<div class="output_wrapper">
	<div class="output">


	<div class="output_area">
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	<div class="output_subarea output_stream output_stdout output_text">
	<pre>Model Details
	=============
	H2OStackedEnsembleEstimator : Stacked Ensemble
	Model Key: StackedEnsemble_AllModels_0_AutoML_20181120_154205
	No model summary for this model


	ModelMetricsBinomialGLM: stackedensemble
	Reported on train data.

	MSE: 0.12685990330985406
	RMSE: 0.3561739789904002
	LogLoss: 0.40703958453227496
	Null degrees of freedom: 130954
	Residual degrees of freedom: 130943
	Null deviance: 124374.13927893189
	Residual deviance: 106607.73758484815
	AIC: 106631.73758484815
	AUC: 0.7734040182726795
	Gini: 0.5468080365453589
	Confusion Matrix (Act/Pred) for max f1 @ threshold = 0.21708051286464972:
	</pre>
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	<div style="overflow:auto"><table style="width:50%"><tr><td><b></b></td>
	<td><b>0</b></td>
	<td><b>1</b></td>
	<td><b>Error</b></td>
	<td><b>Rate</b></td></tr>
	<tr><td>0</td>
	<td>83212.0</td>
	<td>23869.0</td>
	<td>0.2229</td>
	<td> (23869.0/107081.0)</td></tr>
	<tr><td>1</td>
	<td>9376.0</td>
	<td>14498.0</td>
	<td>0.3927</td>
	<td> (9376.0/23874.0)</td></tr>
	<tr><td>Total</td>
	<td>92588.0</td>
	<td>38367.0</td>
	<td>0.2539</td>
	<td> (33245.0/130955.0)</td></tr></table></div>
	</div>

	</div>

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	<pre>Maximum Metrics: Maximum metrics at their respective thresholds

	</pre>
	</div>
	</div>

	<div class="output_area">
	<div class="prompt"></div>


	<div class="output_html rendered_html output_subarea ">
	<div style="overflow:auto"><table style="width:50%"><tr><td><b>metric</b></td>
	<td><b>threshold</b></td>
	<td><b>value</b></td>
	<td><b>idx</b></td></tr>
	<tr><td>max f1</td>
	<td>0.2170805</td>
	<td>0.4658666</td>
	<td>238.0</td></tr>
	<tr><td>max f2</td>
	<td>0.1410190</td>
	<td>0.6067433</td>
	<td>309.0</td></tr>
	<tr><td>max f0point5</td>
	<td>0.3338429</td>
	<td>0.4568693</td>
	<td>155.0</td></tr>
	<tr><td>max accuracy</td>
	<td>0.4390853</td>
	<td>0.8290100</td>
	<td>98.0</td></tr>
	<tr><td>max precision</td>
	<td>0.8006766</td>
	<td>1.0</td>
	<td>0.0</td></tr>
	<tr><td>max recall</td>
	<td>0.0676438</td>
	<td>1.0</td>
	<td>394.0</td></tr>
	<tr><td>max specificity</td>
	<td>0.8006766</td>
	<td>1.0</td>
	<td>0.0</td></tr>
	<tr><td>max absolute_mcc</td>
	<td>0.2335835</td>
	<td>0.3269004</td>
	<td>224.0</td></tr>
	<tr><td>max min_per_class_accuracy</td>
	<td>0.1855661</td>
	<td>0.6993958</td>
	<td>265.0</td></tr>
	<tr><td>max mean_per_class_accuracy</td>
	<td>0.1761337</td>
	<td>0.7006208</td>
	<td>274.0</td></tr></table></div>
	</div>

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	<pre>Gains/Lift Table: Avg response rate: 18.23 %

	</pre>
	</div>
	</div>

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	<div class="output_html rendered_html output_subarea ">
	<div style="overflow:auto"><table style="width:50%"><tr><td><b></b></td>
	<td><b>group</b></td>
	<td><b>cumulative_data_fraction</b></td>
	<td><b>lower_threshold</b></td>
	<td><b>lift</b></td>
	<td><b>cumulative_lift</b></td>
	<td><b>response_rate</b></td>
	<td><b>cumulative_response_rate</b></td>
	<td><b>capture_rate</b></td>
	<td><b>cumulative_capture_rate</b></td>
	<td><b>gain</b></td>
	<td><b>cumulative_gain</b></td></tr>
	<tr><td></td>
	<td>1</td>
	<td>0.0100034</td>
	<td>0.5809896</td>
	<td>4.2290904</td>
	<td>4.2290904</td>
	<td>0.7709924</td>
	<td>0.7709924</td>
	<td>0.0423054</td>
	<td>0.0423054</td>
	<td>322.9090447</td>
	<td>322.9090447</td></tr>
	<tr><td></td>
	<td>2</td>
	<td>0.0200069</td>
	<td>0.5350310</td>
	<td>3.4879528</td>
	<td>3.8585216</td>
	<td>0.6358779</td>
	<td>0.7034351</td>
	<td>0.0348915</td>
	<td>0.0771970</td>
	<td>248.7952815</td>
	<td>285.8521631</td></tr>
	<tr><td></td>
	<td>3</td>
	<td>0.0300027</td>
	<td>0.5007744</td>
	<td>3.1972882</td>
	<td>3.6382227</td>
	<td>0.5828877</td>
	<td>0.6632731</td>
	<td>0.0319595</td>
	<td>0.1091564</td>
	<td>219.7288214</td>
	<td>263.8222689</td></tr>
	<tr><td></td>
	<td>4</td>
	<td>0.0400061</td>
	<td>0.4718430</td>
	<td>2.9436144</td>
	<td>3.4645375</td>
	<td>0.5366412</td>
	<td>0.6316091</td>
	<td>0.0294463</td>
	<td>0.1386027</td>
	<td>194.3614440</td>
	<td>246.4537481</td></tr>
	<tr><td></td>
	<td>5</td>
	<td>0.0500019</td>
	<td>0.4483865</td>
	<td>2.8704357</td>
	<td>3.3457716</td>
	<td>0.5233002</td>
	<td>0.6099572</td>
	<td>0.0286923</td>
	<td>0.1672950</td>
	<td>187.0435684</td>
	<td>234.5771560</td></tr>
	<tr><td></td>
	<td>6</td>
	<td>0.1000038</td>
	<td>0.3623038</td>
	<td>2.4444070</td>
	<td>2.8950893</td>
	<td>0.4456323</td>
	<td>0.5277947</td>
	<td>0.1222250</td>
	<td>0.2895200</td>
	<td>144.4406963</td>
	<td>189.5089261</td></tr>
	<tr><td></td>
	<td>7</td>
	<td>0.1500057</td>
	<td>0.3079302</td>
	<td>1.9878608</td>
	<td>2.5926798</td>
	<td>0.3624007</td>
	<td>0.4726634</td>
	<td>0.0993968</td>
	<td>0.3889168</td>
	<td>98.7860769</td>
	<td>159.2679764</td></tr>
	<tr><td></td>
	<td>8</td>
	<td>0.2</td>
	<td>0.2684456</td>
	<td>1.7116814</td>
	<td>2.3724554</td>
	<td>0.3120513</td>
	<td>0.4325150</td>
	<td>0.0855743</td>
	<td>0.4744911</td>
	<td>71.1681359</td>
	<td>137.2455391</td></tr>
	<tr><td></td>
	<td>9</td>
	<td>0.3000038</td>
	<td>0.2132009</td>
	<td>1.4102670</td>
	<td>2.0517178</td>
	<td>0.2571014</td>
	<td>0.3740423</td>
	<td>0.1410321</td>
	<td>0.6155232</td>
	<td>41.0267006</td>
	<td>105.1717765</td></tr>
	<tr><td></td>
	<td>10</td>
	<td>0.4</td>
	<td>0.1765625</td>
	<td>1.1217652</td>
	<td>1.8192385</td>
	<td>0.2045055</td>
	<td>0.3316597</td>
	<td>0.1121722</td>
	<td>0.7276954</td>
	<td>12.1765206</td>
	<td>81.9238502</td></tr>
	<tr><td></td>
	<td>11</td>
	<td>0.5000038</td>
	<td>0.1503145</td>
	<td>0.8745582</td>
	<td>1.6302967</td>
	<td>0.1594380</td>
	<td>0.2972143</td>
	<td>0.0874592</td>
	<td>0.8151546</td>
	<td>-12.5441786</td>
	<td>63.0296674</td></tr>
	<tr><td></td>
	<td>12</td>
	<td>0.6</td>
	<td>0.1300345</td>
	<td>0.6769128</td>
	<td>1.4714054</td>
	<td>0.1234059</td>
	<td>0.2682474</td>
	<td>0.0676887</td>
	<td>0.8828433</td>
	<td>-32.3087165</td>
	<td>47.1405434</td></tr>
	<tr><td></td>
	<td>13</td>
	<td>0.6999962</td>
	<td>0.1129563</td>
	<td>0.4959559</td>
	<td>1.3320601</td>
	<td>0.0904162</td>
	<td>0.2428437</td>
	<td>0.0495937</td>
	<td>0.9324370</td>
	<td>-50.4044061</td>
	<td>33.2060067</td></tr>
	<tr><td></td>
	<td>14</td>
	<td>0.8</td>
	<td>0.0978849</td>
	<td>0.3920433</td>
	<td>1.2145535</td>
	<td>0.0714722</td>
	<td>0.2214215</td>
	<td>0.0392058</td>
	<td>0.9716428</td>
	<td>-60.7956663</td>
	<td>21.4553489</td></tr>
	<tr><td></td>
	<td>15</td>
	<td>0.8999962</td>
	<td>0.0824531</td>
	<td>0.2194940</td>
	<td>1.1039951</td>
	<td>0.0400153</td>
	<td>0.2012659</td>
	<td>0.0219486</td>
	<td>0.9935914</td>
	<td>-78.0505987</td>
	<td>10.3995078</td></tr>
	<tr><td></td>
	<td>16</td>
	<td>1.0</td>
	<td>0.0597755</td>
	<td>0.0640840</td>
	<td>1.0</td>
	<td>0.0116830</td>
	<td>0.1823069</td>
	<td>0.0064086</td>
	<td>1.0</td>
	<td>-93.5915993</td>
	<td>0.0</td></tr></table></div>
	</div>

	</div>

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	<pre>

	ModelMetricsBinomialGLM: stackedensemble
	Reported on validation data.

	MSE: 0.13813682407268132
	RMSE: 0.37166762580655494
	LogLoss: 0.4379927029517987
	Null degrees of freedom: 33031
	Residual degrees of freedom: 33020
	Null deviance: 31732.354674481932
	Residual deviance: 28935.54992780763
	AIC: 28959.54992780763
	AUC: 0.7122628231156057
	Gini: 0.4245256462312115
	Confusion Matrix (Act/Pred) for max f1 @ threshold = 0.18933454821029921:
	</pre>
	</div>
	</div>

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	<div class="output_html rendered_html output_subarea ">
	<div style="overflow:auto"><table style="width:50%"><tr><td><b></b></td>
	<td><b>0</b></td>
	<td><b>1</b></td>
	<td><b>Error</b></td>
	<td><b>Rate</b></td></tr>
	<tr><td>0</td>
	<td>18652.0</td>
	<td>8238.0</td>
	<td>0.3064</td>
	<td> (8238.0/26890.0)</td></tr>
	<tr><td>1</td>
	<td>2386.0</td>
	<td>3756.0</td>
	<td>0.3885</td>
	<td> (2386.0/6142.0)</td></tr>
	<tr><td>Total</td>
	<td>21038.0</td>
	<td>11994.0</td>
	<td>0.3216</td>
	<td> (10624.0/33032.0)</td></tr></table></div>
	</div>

	</div>

	<div class="output_area">
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	<div class="output_subarea output_stream output_stdout output_text">
	<pre>Maximum Metrics: Maximum metrics at their respective thresholds

	</pre>
	</div>
	</div>

	<div class="output_area">
	<div class="prompt"></div>


	<div class="output_html rendered_html output_subarea ">
	<div style="overflow:auto"><table style="width:50%"><tr><td><b>metric</b></td>
	<td><b>threshold</b></td>
	<td><b>value</b></td>
	<td><b>idx</b></td></tr>
	<tr><td>max f1</td>
	<td>0.1893345</td>
	<td>0.4142038</td>
	<td>256.0</td></tr>
	<tr><td>max f2</td>
	<td>0.1197407</td>
	<td>0.5738535</td>
	<td>330.0</td></tr>
	<tr><td>max f0point5</td>
	<td>0.3129965</td>
	<td>0.3817812</td>
	<td>160.0</td></tr>
	<tr><td>max accuracy</td>
	<td>0.6010242</td>
	<td>0.8160572</td>
	<td>29.0</td></tr>
	<tr><td>max precision</td>
	<td>0.7666583</td>
	<td>1.0</td>
	<td>0.0</td></tr>
	<tr><td>max recall</td>
	<td>0.0640080</td>
	<td>1.0</td>
	<td>398.0</td></tr>
	<tr><td>max specificity</td>
	<td>0.7666583</td>
	<td>1.0</td>
	<td>0.0</td></tr>
	<tr><td>max absolute_mcc</td>
	<td>0.2092723</td>
	<td>0.2475688</td>
	<td>238.0</td></tr>
	<tr><td>max min_per_class_accuracy</td>
	<td>0.1762849</td>
	<td>0.6525562</td>
	<td>268.0</td></tr>
	<tr><td>max mean_per_class_accuracy</td>
	<td>0.1577331</td>
	<td>0.6547886</td>
	<td>286.0</td></tr></table></div>
	</div>

	</div>

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	<pre>Gains/Lift Table: Avg response rate: 18.59 %

	</pre>
	</div>
	</div>

	<div class="output_area">
	<div class="prompt"></div>


	<div class="output_html rendered_html output_subarea ">
	<div style="overflow:auto"><table style="width:50%"><tr><td><b></b></td>
	<td><b>group</b></td>
	<td><b>cumulative_data_fraction</b></td>
	<td><b>lower_threshold</b></td>
	<td><b>lift</b></td>
	<td><b>cumulative_lift</b></td>
	<td><b>response_rate</b></td>
	<td><b>cumulative_response_rate</b></td>
	<td><b>capture_rate</b></td>
	<td><b>cumulative_capture_rate</b></td>
	<td><b>gain</b></td>
	<td><b>cumulative_gain</b></td></tr>
	<tr><td></td>
	<td>1</td>
	<td>0.0100206</td>
	<td>0.5783690</td>
	<td>3.1358434</td>
	<td>3.1358434</td>
	<td>0.5830816</td>
	<td>0.5830816</td>
	<td>0.0314230</td>
	<td>0.0314230</td>
	<td>213.5843447</td>
	<td>213.5843447</td></tr>
	<tr><td></td>
	<td>2</td>
	<td>0.0200109</td>
	<td>0.5293169</td>
	<td>2.5749465</td>
	<td>2.8558192</td>
	<td>0.4787879</td>
	<td>0.5310136</td>
	<td>0.0257245</td>
	<td>0.0571475</td>
	<td>157.4946469</td>
	<td>185.5819237</td></tr>
	<tr><td></td>
	<td>3</td>
	<td>0.0300012</td>
	<td>0.4955180</td>
	<td>2.4119752</td>
	<td>2.7080205</td>
	<td>0.4484848</td>
	<td>0.5035318</td>
	<td>0.0240964</td>
	<td>0.0812439</td>
	<td>141.1975173</td>
	<td>170.8020508</td></tr>
	<tr><td></td>
	<td>4</td>
	<td>0.0400218</td>
	<td>0.4688250</td>
	<td>2.4859277</td>
	<td>2.6524133</td>
	<td>0.4622356</td>
	<td>0.4931921</td>
	<td>0.0249105</td>
	<td>0.1061543</td>
	<td>148.5927707</td>
	<td>165.2413309</td></tr>
	<tr><td></td>
	<td>5</td>
	<td>0.0500121</td>
	<td>0.4455599</td>
	<td>2.2164096</td>
	<td>2.5653181</td>
	<td>0.4121212</td>
	<td>0.4769976</td>
	<td>0.0221426</td>
	<td>0.1282970</td>
	<td>121.6409619</td>
	<td>156.5318141</td></tr>
	<tr><td></td>
	<td>6</td>
	<td>0.1000242</td>
	<td>0.3612868</td>
	<td>2.0607188</td>
	<td>2.3130185</td>
	<td>0.3831719</td>
	<td>0.4300847</td>
	<td>0.1030609</td>
	<td>0.2313579</td>
	<td>106.0718760</td>
	<td>131.3018450</td></tr>
	<tr><td></td>
	<td>7</td>
	<td>0.1500061</td>
	<td>0.3068785</td>
	<td>1.7850835</td>
	<td>2.1371112</td>
	<td>0.3319200</td>
	<td>0.3973764</td>
	<td>0.0892218</td>
	<td>0.3205796</td>
	<td>78.5083530</td>
	<td>113.7111174</td></tr>
	<tr><td></td>
	<td>8</td>
	<td>0.2000182</td>
	<td>0.2675737</td>
	<td>1.5756523</td>
	<td>1.9967252</td>
	<td>0.2929782</td>
	<td>0.3712729</td>
	<td>0.0788017</td>
	<td>0.3993813</td>
	<td>57.5652259</td>
	<td>99.6725200</td></tr>
	<tr><td></td>
	<td>9</td>
	<td>0.3000121</td>
	<td>0.2132448</td>
	<td>1.3758567</td>
	<td>1.7897899</td>
	<td>0.2558280</td>
	<td>0.3327952</td>
	<td>0.1375773</td>
	<td>0.5369586</td>
	<td>37.5856668</td>
	<td>78.9789907</td></tr>
	<tr><td></td>
	<td>10</td>
	<td>0.4000061</td>
	<td>0.1764937</td>
	<td>1.1299935</td>
	<td>1.6248533</td>
	<td>0.2101120</td>
	<td>0.3021267</td>
	<td>0.1129925</td>
	<td>0.6499512</td>
	<td>12.9993524</td>
	<td>62.4853295</td></tr>
	<tr><td></td>
	<td>11</td>
	<td>0.5</td>
	<td>0.1497263</td>
	<td>0.9964784</td>
	<td>1.4991859</td>
	<td>0.1852861</td>
	<td>0.2787600</td>
	<td>0.0996418</td>
	<td>0.7495930</td>
	<td>-0.3521561</td>
	<td>49.9185933</td></tr>
	<tr><td></td>
	<td>12</td>
	<td>0.5999939</td>
	<td>0.1296393</td>
	<td>0.7587565</td>
	<td>1.3757872</td>
	<td>0.1410839</td>
	<td>0.2558151</td>
	<td>0.0758711</td>
	<td>0.8254640</td>
	<td>-24.1243542</td>
	<td>37.5787247</td></tr>
	<tr><td></td>
	<td>13</td>
	<td>0.6999879</td>
	<td>0.1130667</td>
	<td>0.6284978</td>
	<td>1.2690362</td>
	<td>0.1168635</td>
	<td>0.2359657</td>
	<td>0.0628460</td>
	<td>0.8883100</td>
	<td>-37.1502161</td>
	<td>26.9036234</td></tr>
	<tr><td></td>
	<td>14</td>
	<td>0.7999818</td>
	<td>0.0982229</td>
	<td>0.5259192</td>
	<td>1.1761501</td>
	<td>0.0977899</td>
	<td>0.2186944</td>
	<td>0.0525887</td>
	<td>0.9408987</td>
	<td>-47.4080824</td>
	<td>17.6150117</td></tr>
	<tr><td></td>
	<td>15</td>
	<td>0.8999758</td>
	<td>0.0826149</td>
	<td>0.3989170</td>
	<td>1.0897938</td>
	<td>0.0741750</td>
	<td>0.2026372</td>
	<td>0.0398893</td>
	<td>0.9807880</td>
	<td>-60.1082978</td>
	<td>8.9793790</td></tr>
	<tr><td></td>
	<td>16</td>
	<td>1.0</td>
	<td>0.0605773</td>
	<td>0.1920733</td>
	<td>1.0</td>
	<td>0.0357143</td>
	<td>0.1859409</td>
	<td>0.0192120</td>
	<td>1.0</td>
	<td>-80.7926687</td>
	<td>0.0</td></tr></table></div>
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	ModelMetricsBinomialGLM: stackedensemble
	Reported on cross-validation data.

	MSE: 0.1369765435568584
	RMSE: 0.3701034227845757
	LogLoss: 0.4355309009590542
	Null degrees of freedom: 130954
	Residual degrees of freedom: 130943
	Null deviance: 124375.46514588114
	Residual deviance: 114069.89827018589
	AIC: 114093.89827018589
	AUC: 0.7071203432205223
	Gini: 0.4142406864410446
	Confusion Matrix (Act/Pred) for max f1 @ threshold = 0.17843972441369682:
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	<div style="overflow:auto"><table style="width:50%"><tr><td><b></b></td>
	<td><b>0</b></td>
	<td><b>1</b></td>
	<td><b>Error</b></td>
	<td><b>Rate</b></td></tr>
	<tr><td>0</td>
	<td>73561.0</td>
	<td>33520.0</td>
	<td>0.313</td>
	<td> (33520.0/107081.0)</td></tr>
	<tr><td>1</td>
	<td>9215.0</td>
	<td>14659.0</td>
	<td>0.386</td>
	<td> (9215.0/23874.0)</td></tr>
	<tr><td>Total</td>
	<td>82776.0</td>
	<td>48179.0</td>
	<td>0.3263</td>
	<td> (42735.0/130955.0)</td></tr></table></div>
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	<pre>Maximum Metrics: Maximum metrics at their respective thresholds

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	<div style="overflow:auto"><table style="width:50%"><tr><td><b>metric</b></td>
	<td><b>threshold</b></td>
	<td><b>value</b></td>
	<td><b>idx</b></td></tr>
	<tr><td>max f1</td>
	<td>0.1784397</td>
	<td>0.4068949</td>
	<td>261.0</td></tr>
	<tr><td>max f2</td>
	<td>0.1136746</td>
	<td>0.5665672</td>
	<td>334.0</td></tr>
	<tr><td>max f0point5</td>
	<td>0.2879939</td>
	<td>0.3708050</td>
	<td>176.0</td></tr>
	<tr><td>max accuracy</td>
	<td>0.5663591</td>
	<td>0.8184567</td>
	<td>36.0</td></tr>
	<tr><td>max precision</td>
	<td>0.7859236</td>
	<td>1.0</td>
	<td>0.0</td></tr>
	<tr><td>max recall</td>
	<td>0.0620870</td>
	<td>1.0</td>
	<td>399.0</td></tr>
	<tr><td>max specificity</td>
	<td>0.7859236</td>
	<td>1.0</td>
	<td>0.0</td></tr>
	<tr><td>max absolute_mcc</td>
	<td>0.1815977</td>
	<td>0.2412252</td>
	<td>258.0</td></tr>
	<tr><td>max min_per_class_accuracy</td>
	<td>0.1671726</td>
	<td>0.6498819</td>
	<td>272.0</td></tr>
	<tr><td>max mean_per_class_accuracy</td>
	<td>0.1616542</td>
	<td>0.6512829</td>
	<td>278.0</td></tr></table></div>
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	<pre>Gains/Lift Table: Avg response rate: 18.23 %

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	<div style="overflow:auto"><table style="width:50%"><tr><td><b></b></td>
	<td><b>group</b></td>
	<td><b>cumulative_data_fraction</b></td>
	<td><b>lower_threshold</b></td>
	<td><b>lift</b></td>
	<td><b>cumulative_lift</b></td>
	<td><b>response_rate</b></td>
	<td><b>cumulative_response_rate</b></td>
	<td><b>capture_rate</b></td>
	<td><b>cumulative_capture_rate</b></td>
	<td><b>gain</b></td>
	<td><b>cumulative_gain</b></td></tr>
	<tr><td></td>
	<td>1</td>
	<td>0.0100034</td>
	<td>0.5609815</td>
	<td>2.9394272</td>
	<td>2.9394272</td>
	<td>0.5358779</td>
	<td>0.5358779</td>
	<td>0.0294044</td>
	<td>0.0294044</td>
	<td>193.9427222</td>
	<td>193.9427222</td></tr>
	<tr><td></td>
	<td>2</td>
	<td>0.0200069</td>
	<td>0.5136764</td>
	<td>2.6044498</td>
	<td>2.7719385</td>
	<td>0.4748092</td>
	<td>0.5053435</td>
	<td>0.0260534</td>
	<td>0.0554578</td>
	<td>160.4449761</td>
	<td>177.1938491</td></tr>
	<tr><td></td>
	<td>3</td>
	<td>0.0300027</td>
	<td>0.4802174</td>
	<td>2.4346323</td>
	<td>2.6595603</td>
	<td>0.4438503</td>
	<td>0.4848562</td>
	<td>0.0243361</td>
	<td>0.0797939</td>
	<td>143.4632310</td>
	<td>165.9560331</td></tr>
	<tr><td></td>
	<td>4</td>
	<td>0.0400061</td>
	<td>0.4541967</td>
	<td>2.2987828</td>
	<td>2.5693487</td>
	<td>0.4190840</td>
	<td>0.4684100</td>
	<td>0.0229957</td>
	<td>0.1027896</td>
	<td>129.8782827</td>
	<td>156.9348739</td></tr>
	<tr><td></td>
	<td>5</td>
	<td>0.0500019</td>
	<td>0.4304407</td>
	<td>2.3592048</td>
	<td>2.5273392</td>
	<td>0.4300993</td>
	<td>0.4607514</td>
	<td>0.0235821</td>
	<td>0.1263718</td>
	<td>135.9204803</td>
	<td>152.7339208</td></tr>
	<tr><td></td>
	<td>6</td>
	<td>0.1000038</td>
	<td>0.3489922</td>
	<td>2.0674422</td>
	<td>2.2973907</td>
	<td>0.3769090</td>
	<td>0.4188302</td>
	<td>0.1033761</td>
	<td>0.2297478</td>
	<td>106.7442216</td>
	<td>129.7390712</td></tr>
	<tr><td></td>
	<td>7</td>
	<td>0.1500057</td>
	<td>0.2957391</td>
	<td>1.7583311</td>
	<td>2.1177042</td>
	<td>0.3205559</td>
	<td>0.3860721</td>
	<td>0.0879199</td>
	<td>0.3176678</td>
	<td>75.8331123</td>
	<td>111.7704182</td></tr>
	<tr><td></td>
	<td>8</td>
	<td>0.2</td>
	<td>0.2569097</td>
	<td>1.5826559</td>
	<td>1.9839574</td>
	<td>0.2885291</td>
	<td>0.3616891</td>
	<td>0.0791237</td>
	<td>0.3967915</td>
	<td>58.2655941</td>
	<td>98.3957443</td></tr>
	<tr><td></td>
	<td>9</td>
	<td>0.3000038</td>
	<td>0.2032167</td>
	<td>1.3679632</td>
	<td>1.7786208</td>
	<td>0.2493891</td>
	<td>0.3242548</td>
	<td>0.1368015</td>
	<td>0.5335930</td>
	<td>36.7963184</td>
	<td>77.8620797</td></tr>
	<tr><td></td>
	<td>10</td>
	<td>0.4</td>
	<td>0.1679941</td>
	<td>1.1284673</td>
	<td>1.6160886</td>
	<td>0.2057274</td>
	<td>0.2946241</td>
	<td>0.1128424</td>
	<td>0.6464355</td>
	<td>12.8467313</td>
	<td>61.6088632</td></tr>
	<tr><td></td>
	<td>11</td>
	<td>0.5000038</td>
	<td>0.1428590</td>
	<td>0.9302652</td>
	<td>1.4789198</td>
	<td>0.1695938</td>
	<td>0.2696173</td>
	<td>0.0930301</td>
	<td>0.7394655</td>
	<td>-6.9734773</td>
	<td>47.8919761</td></tr>
	<tr><td></td>
	<td>12</td>
	<td>0.6</td>
	<td>0.1238863</td>
	<td>0.8143060</td>
	<td>1.3681550</td>
	<td>0.1484536</td>
	<td>0.2494241</td>
	<td>0.0814275</td>
	<td>0.8208930</td>
	<td>-18.5693965</td>
	<td>36.8155036</td></tr>
	<tr><td></td>
	<td>13</td>
	<td>0.6999962</td>
	<td>0.1081113</td>
	<td>0.6589009</td>
	<td>1.2668363</td>
	<td>0.1201222</td>
	<td>0.2309530</td>
	<td>0.0658876</td>
	<td>0.8867806</td>
	<td>-34.1099078</td>
	<td>26.6836336</td></tr>
	<tr><td></td>
	<td>14</td>
	<td>0.8</td>
	<td>0.0941428</td>
	<td>0.5185360</td>
	<td>1.1732952</td>
	<td>0.0945327</td>
	<td>0.2138998</td>
	<td>0.0518556</td>
	<td>0.9386362</td>
	<td>-48.1464047</td>
	<td>17.3295217</td></tr>
	<tr><td></td>
	<td>15</td>
	<td>0.8999962</td>
	<td>0.0801775</td>
	<td>0.3945866</td>
	<td>1.0867750</td>
	<td>0.0719359</td>
	<td>0.1981266</td>
	<td>0.0394572</td>
	<td>0.9780933</td>
	<td>-60.5413434</td>
	<td>8.6774970</td></tr>
	<tr><td></td>
	<td>16</td>
	<td>1.0</td>
	<td>0.0597666</td>
	<td>0.2190584</td>
	<td>1.0</td>
	<td>0.0399359</td>
	<td>0.1823069</td>
	<td>0.0219067</td>
	<td>1.0</td>
	<td>-78.0941597</td>
	<td>0.0</td></tr></table></div>
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	<pre><bound method H2OBinomialModel.tnr of ></pre>
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	<div class=" highlight hl-ipython3"><pre><span></span><span class="n">aml</span><span class="o">.</span><span class="n">leader</span><span class="o">.</span><span class="n">tpr</span>
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	<pre>Model Details
	=============
	H2OStackedEnsembleEstimator : Stacked Ensemble
	Model Key: StackedEnsemble_AllModels_0_AutoML_20181120_154205
	No model summary for this model


	ModelMetricsBinomialGLM: stackedensemble
	Reported on train data.

	MSE: 0.12685990330985406
	RMSE: 0.3561739789904002
	LogLoss: 0.40703958453227496
	Null degrees of freedom: 130954
	Residual degrees of freedom: 130943
	Null deviance: 124374.13927893189
	Residual deviance: 106607.73758484815
	AIC: 106631.73758484815
	AUC: 0.7734040182726795
	Gini: 0.5468080365453589
	Confusion Matrix (Act/Pred) for max f1 @ threshold = 0.21708051286464972:
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	<div style="overflow:auto"><table style="width:50%"><tr><td><b></b></td>
	<td><b>0</b></td>
	<td><b>1</b></td>
	<td><b>Error</b></td>
	<td><b>Rate</b></td></tr>
	<tr><td>0</td>
	<td>83212.0</td>
	<td>23869.0</td>
	<td>0.2229</td>
	<td> (23869.0/107081.0)</td></tr>
	<tr><td>1</td>
	<td>9376.0</td>
	<td>14498.0</td>
	<td>0.3927</td>
	<td> (9376.0/23874.0)</td></tr>
	<tr><td>Total</td>
	<td>92588.0</td>
	<td>38367.0</td>
	<td>0.2539</td>
	<td> (33245.0/130955.0)</td></tr></table></div>
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	<pre>Maximum Metrics: Maximum metrics at their respective thresholds

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	</div>
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	<div style="overflow:auto"><table style="width:50%"><tr><td><b>metric</b></td>
	<td><b>threshold</b></td>
	<td><b>value</b></td>
	<td><b>idx</b></td></tr>
	<tr><td>max f1</td>
	<td>0.2170805</td>
	<td>0.4658666</td>
	<td>238.0</td></tr>
	<tr><td>max f2</td>
	<td>0.1410190</td>
	<td>0.6067433</td>
	<td>309.0</td></tr>
	<tr><td>max f0point5</td>
	<td>0.3338429</td>
	<td>0.4568693</td>
	<td>155.0</td></tr>
	<tr><td>max accuracy</td>
	<td>0.4390853</td>
	<td>0.8290100</td>
	<td>98.0</td></tr>
	<tr><td>max precision</td>
	<td>0.8006766</td>
	<td>1.0</td>
	<td>0.0</td></tr>
	<tr><td>max recall</td>
	<td>0.0676438</td>
	<td>1.0</td>
	<td>394.0</td></tr>
	<tr><td>max specificity</td>
	<td>0.8006766</td>
	<td>1.0</td>
	<td>0.0</td></tr>
	<tr><td>max absolute_mcc</td>
	<td>0.2335835</td>
	<td>0.3269004</td>
	<td>224.0</td></tr>
	<tr><td>max min_per_class_accuracy</td>
	<td>0.1855661</td>
	<td>0.6993958</td>
	<td>265.0</td></tr>
	<tr><td>max mean_per_class_accuracy</td>
	<td>0.1761337</td>
	<td>0.7006208</td>
	<td>274.0</td></tr></table></div>
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	<pre>Gains/Lift Table: Avg response rate: 18.23 %

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	<td><b>group</b></td>
	<td><b>cumulative_data_fraction</b></td>
	<td><b>lower_threshold</b></td>
	<td><b>lift</b></td>
	<td><b>cumulative_lift</b></td>
	<td><b>response_rate</b></td>
	<td><b>cumulative_response_rate</b></td>
	<td><b>capture_rate</b></td>
	<td><b>cumulative_capture_rate</b></td>
	<td><b>gain</b></td>
	<td><b>cumulative_gain</b></td></tr>
	<tr><td></td>
	<td>1</td>
	<td>0.0100034</td>
	<td>0.5809896</td>
	<td>4.2290904</td>
	<td>4.2290904</td>
	<td>0.7709924</td>
	<td>0.7709924</td>
	<td>0.0423054</td>
	<td>0.0423054</td>
	<td>322.9090447</td>
	<td>322.9090447</td></tr>
	<tr><td></td>
	<td>2</td>
	<td>0.0200069</td>
	<td>0.5350310</td>
	<td>3.4879528</td>
	<td>3.8585216</td>
	<td>0.6358779</td>
	<td>0.7034351</td>
	<td>0.0348915</td>
	<td>0.0771970</td>
	<td>248.7952815</td>
	<td>285.8521631</td></tr>
	<tr><td></td>
	<td>3</td>
	<td>0.0300027</td>
	<td>0.5007744</td>
	<td>3.1972882</td>
	<td>3.6382227</td>
	<td>0.5828877</td>
	<td>0.6632731</td>
	<td>0.0319595</td>
	<td>0.1091564</td>
	<td>219.7288214</td>
	<td>263.8222689</td></tr>
	<tr><td></td>
	<td>4</td>
	<td>0.0400061</td>
	<td>0.4718430</td>
	<td>2.9436144</td>
	<td>3.4645375</td>
	<td>0.5366412</td>
	<td>0.6316091</td>
	<td>0.0294463</td>
	<td>0.1386027</td>
	<td>194.3614440</td>
	<td>246.4537481</td></tr>
	<tr><td></td>
	<td>5</td>
	<td>0.0500019</td>
	<td>0.4483865</td>
	<td>2.8704357</td>
	<td>3.3457716</td>
	<td>0.5233002</td>
	<td>0.6099572</td>
	<td>0.0286923</td>
	<td>0.1672950</td>
	<td>187.0435684</td>
	<td>234.5771560</td></tr>
	<tr><td></td>
	<td>6</td>
	<td>0.1000038</td>
	<td>0.3623038</td>
	<td>2.4444070</td>
	<td>2.8950893</td>
	<td>0.4456323</td>
	<td>0.5277947</td>
	<td>0.1222250</td>
	<td>0.2895200</td>
	<td>144.4406963</td>
	<td>189.5089261</td></tr>
	<tr><td></td>
	<td>7</td>
	<td>0.1500057</td>
	<td>0.3079302</td>
	<td>1.9878608</td>
	<td>2.5926798</td>
	<td>0.3624007</td>
	<td>0.4726634</td>
	<td>0.0993968</td>
	<td>0.3889168</td>
	<td>98.7860769</td>
	<td>159.2679764</td></tr>
	<tr><td></td>
	<td>8</td>
	<td>0.2</td>
	<td>0.2684456</td>
	<td>1.7116814</td>
	<td>2.3724554</td>
	<td>0.3120513</td>
	<td>0.4325150</td>
	<td>0.0855743</td>
	<td>0.4744911</td>
	<td>71.1681359</td>
	<td>137.2455391</td></tr>
	<tr><td></td>
	<td>9</td>
	<td>0.3000038</td>
	<td>0.2132009</td>
	<td>1.4102670</td>
	<td>2.0517178</td>
	<td>0.2571014</td>
	<td>0.3740423</td>
	<td>0.1410321</td>
	<td>0.6155232</td>
	<td>41.0267006</td>
	<td>105.1717765</td></tr>
	<tr><td></td>
	<td>10</td>
	<td>0.4</td>
	<td>0.1765625</td>
	<td>1.1217652</td>
	<td>1.8192385</td>
	<td>0.2045055</td>
	<td>0.3316597</td>
	<td>0.1121722</td>
	<td>0.7276954</td>
	<td>12.1765206</td>
	<td>81.9238502</td></tr>
	<tr><td></td>
	<td>11</td>
	<td>0.5000038</td>
	<td>0.1503145</td>
	<td>0.8745582</td>
	<td>1.6302967</td>
	<td>0.1594380</td>
	<td>0.2972143</td>
	<td>0.0874592</td>
	<td>0.8151546</td>
	<td>-12.5441786</td>
	<td>63.0296674</td></tr>
	<tr><td></td>
	<td>12</td>
	<td>0.6</td>
	<td>0.1300345</td>
	<td>0.6769128</td>
	<td>1.4714054</td>
	<td>0.1234059</td>
	<td>0.2682474</td>
	<td>0.0676887</td>
	<td>0.8828433</td>
	<td>-32.3087165</td>
	<td>47.1405434</td></tr>
	<tr><td></td>
	<td>13</td>
	<td>0.6999962</td>
	<td>0.1129563</td>
	<td>0.4959559</td>
	<td>1.3320601</td>
	<td>0.0904162</td>
	<td>0.2428437</td>
	<td>0.0495937</td>
	<td>0.9324370</td>
	<td>-50.4044061</td>
	<td>33.2060067</td></tr>
	<tr><td></td>
	<td>14</td>
	<td>0.8</td>
	<td>0.0978849</td>
	<td>0.3920433</td>
	<td>1.2145535</td>
	<td>0.0714722</td>
	<td>0.2214215</td>
	<td>0.0392058</td>
	<td>0.9716428</td>
	<td>-60.7956663</td>
	<td>21.4553489</td></tr>
	<tr><td></td>
	<td>15</td>
	<td>0.8999962</td>
	<td>0.0824531</td>
	<td>0.2194940</td>
	<td>1.1039951</td>
	<td>0.0400153</td>
	<td>0.2012659</td>
	<td>0.0219486</td>
	<td>0.9935914</td>
	<td>-78.0505987</td>
	<td>10.3995078</td></tr>
	<tr><td></td>
	<td>16</td>
	<td>1.0</td>
	<td>0.0597755</td>
	<td>0.0640840</td>
	<td>1.0</td>
	<td>0.0116830</td>
	<td>0.1823069</td>
	<td>0.0064086</td>
	<td>1.0</td>
	<td>-93.5915993</td>
	<td>0.0</td></tr></table></div>
	</div>

	</div>

	<div class="output_area">
	<div class="prompt"></div>

	<div class="output_subarea output_stream output_stdout output_text">
	<pre>

	ModelMetricsBinomialGLM: stackedensemble
	Reported on validation data.

	MSE: 0.13813682407268132
	RMSE: 0.37166762580655494
	LogLoss: 0.4379927029517987
	Null degrees of freedom: 33031
	Residual degrees of freedom: 33020
	Null deviance: 31732.354674481932
	Residual deviance: 28935.54992780763
	AIC: 28959.54992780763
	AUC: 0.7122628231156057
	Gini: 0.4245256462312115
	Confusion Matrix (Act/Pred) for max f1 @ threshold = 0.18933454821029921:
	</pre>
	</div>
	</div>

	<div class="output_area">
	<div class="prompt"></div>


	<div class="output_html rendered_html output_subarea ">
	<div style="overflow:auto"><table style="width:50%"><tr><td><b></b></td>
	<td><b>0</b></td>
	<td><b>1</b></td>
	<td><b>Error</b></td>
	<td><b>Rate</b></td></tr>
	<tr><td>0</td>
	<td>18652.0</td>
	<td>8238.0</td>
	<td>0.3064</td>
	<td> (8238.0/26890.0)</td></tr>
	<tr><td>1</td>
	<td>2386.0</td>
	<td>3756.0</td>
	<td>0.3885</td>
	<td> (2386.0/6142.0)</td></tr>
	<tr><td>Total</td>
	<td>21038.0</td>
	<td>11994.0</td>
	<td>0.3216</td>
	<td> (10624.0/33032.0)</td></tr></table></div>
	</div>

	</div>

	<div class="output_area">
	<div class="prompt"></div>

	<div class="output_subarea output_stream output_stdout output_text">
	<pre>Maximum Metrics: Maximum metrics at their respective thresholds

	</pre>
	</div>
	</div>

	<div class="output_area">
	<div class="prompt"></div>


	<div class="output_html rendered_html output_subarea ">
	<div style="overflow:auto"><table style="width:50%"><tr><td><b>metric</b></td>
	<td><b>threshold</b></td>
	<td><b>value</b></td>
	<td><b>idx</b></td></tr>
	<tr><td>max f1</td>
	<td>0.1893345</td>
	<td>0.4142038</td>
	<td>256.0</td></tr>
	<tr><td>max f2</td>
	<td>0.1197407</td>
	<td>0.5738535</td>
	<td>330.0</td></tr>
	<tr><td>max f0point5</td>
	<td>0.3129965</td>
	<td>0.3817812</td>
	<td>160.0</td></tr>
	<tr><td>max accuracy</td>
	<td>0.6010242</td>
	<td>0.8160572</td>
	<td>29.0</td></tr>
	<tr><td>max precision</td>
	<td>0.7666583</td>
	<td>1.0</td>
	<td>0.0</td></tr>
	<tr><td>max recall</td>
	<td>0.0640080</td>
	<td>1.0</td>
	<td>398.0</td></tr>
	<tr><td>max specificity</td>
	<td>0.7666583</td>
	<td>1.0</td>
	<td>0.0</td></tr>
	<tr><td>max absolute_mcc</td>
	<td>0.2092723</td>
	<td>0.2475688</td>
	<td>238.0</td></tr>
	<tr><td>max min_per_class_accuracy</td>
	<td>0.1762849</td>
	<td>0.6525562</td>
	<td>268.0</td></tr>
	<tr><td>max mean_per_class_accuracy</td>
	<td>0.1577331</td>
	<td>0.6547886</td>
	<td>286.0</td></tr></table></div>
	</div>

	</div>

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	<div class="prompt"></div>

	<div class="output_subarea output_stream output_stdout output_text">
	<pre>Gains/Lift Table: Avg response rate: 18.59 %

	</pre>
	</div>
	</div>

	<div class="output_area">
	<div class="prompt"></div>


	<div class="output_html rendered_html output_subarea ">
	<div style="overflow:auto"><table style="width:50%"><tr><td><b></b></td>
	<td><b>group</b></td>
	<td><b>cumulative_data_fraction</b></td>
	<td><b>lower_threshold</b></td>
	<td><b>lift</b></td>
	<td><b>cumulative_lift</b></td>
	<td><b>response_rate</b></td>
	<td><b>cumulative_response_rate</b></td>
	<td><b>capture_rate</b></td>
	<td><b>cumulative_capture_rate</b></td>
	<td><b>gain</b></td>
	<td><b>cumulative_gain</b></td></tr>
	<tr><td></td>
	<td>1</td>
	<td>0.0100206</td>
	<td>0.5783690</td>
	<td>3.1358434</td>
	<td>3.1358434</td>
	<td>0.5830816</td>
	<td>0.5830816</td>
	<td>0.0314230</td>
	<td>0.0314230</td>
	<td>213.5843447</td>
	<td>213.5843447</td></tr>
	<tr><td></td>
	<td>2</td>
	<td>0.0200109</td>
	<td>0.5293169</td>
	<td>2.5749465</td>
	<td>2.8558192</td>
	<td>0.4787879</td>
	<td>0.5310136</td>
	<td>0.0257245</td>
	<td>0.0571475</td>
	<td>157.4946469</td>
	<td>185.5819237</td></tr>
	<tr><td></td>
	<td>3</td>
	<td>0.0300012</td>
	<td>0.4955180</td>
	<td>2.4119752</td>
	<td>2.7080205</td>
	<td>0.4484848</td>
	<td>0.5035318</td>
	<td>0.0240964</td>
	<td>0.0812439</td>
	<td>141.1975173</td>
	<td>170.8020508</td></tr>
	<tr><td></td>
	<td>4</td>
	<td>0.0400218</td>
	<td>0.4688250</td>
	<td>2.4859277</td>
	<td>2.6524133</td>
	<td>0.4622356</td>
	<td>0.4931921</td>
	<td>0.0249105</td>
	<td>0.1061543</td>
	<td>148.5927707</td>
	<td>165.2413309</td></tr>
	<tr><td></td>
	<td>5</td>
	<td>0.0500121</td>
	<td>0.4455599</td>
	<td>2.2164096</td>
	<td>2.5653181</td>
	<td>0.4121212</td>
	<td>0.4769976</td>
	<td>0.0221426</td>
	<td>0.1282970</td>
	<td>121.6409619</td>
	<td>156.5318141</td></tr>
	<tr><td></td>
	<td>6</td>
	<td>0.1000242</td>
	<td>0.3612868</td>
	<td>2.0607188</td>
	<td>2.3130185</td>
	<td>0.3831719</td>
	<td>0.4300847</td>
	<td>0.1030609</td>
	<td>0.2313579</td>
	<td>106.0718760</td>
	<td>131.3018450</td></tr>
	<tr><td></td>
	<td>7</td>
	<td>0.1500061</td>
	<td>0.3068785</td>
	<td>1.7850835</td>
	<td>2.1371112</td>
	<td>0.3319200</td>
	<td>0.3973764</td>
	<td>0.0892218</td>
	<td>0.3205796</td>
	<td>78.5083530</td>
	<td>113.7111174</td></tr>
	<tr><td></td>
	<td>8</td>
	<td>0.2000182</td>
	<td>0.2675737</td>
	<td>1.5756523</td>
	<td>1.9967252</td>
	<td>0.2929782</td>
	<td>0.3712729</td>
	<td>0.0788017</td>
	<td>0.3993813</td>
	<td>57.5652259</td>
	<td>99.6725200</td></tr>
	<tr><td></td>
	<td>9</td>
	<td>0.3000121</td>
	<td>0.2132448</td>
	<td>1.3758567</td>
	<td>1.7897899</td>
	<td>0.2558280</td>
	<td>0.3327952</td>
	<td>0.1375773</td>
	<td>0.5369586</td>
	<td>37.5856668</td>
	<td>78.9789907</td></tr>
	<tr><td></td>
	<td>10</td>
	<td>0.4000061</td>
	<td>0.1764937</td>
	<td>1.1299935</td>
	<td>1.6248533</td>
	<td>0.2101120</td>
	<td>0.3021267</td>
	<td>0.1129925</td>
	<td>0.6499512</td>
	<td>12.9993524</td>
	<td>62.4853295</td></tr>
	<tr><td></td>
	<td>11</td>
	<td>0.5</td>
	<td>0.1497263</td>
	<td>0.9964784</td>
	<td>1.4991859</td>
	<td>0.1852861</td>
	<td>0.2787600</td>
	<td>0.0996418</td>
	<td>0.7495930</td>
	<td>-0.3521561</td>
	<td>49.9185933</td></tr>
	<tr><td></td>
	<td>12</td>
	<td>0.5999939</td>
	<td>0.1296393</td>
	<td>0.7587565</td>
	<td>1.3757872</td>
	<td>0.1410839</td>
	<td>0.2558151</td>
	<td>0.0758711</td>
	<td>0.8254640</td>
	<td>-24.1243542</td>
	<td>37.5787247</td></tr>
	<tr><td></td>
	<td>13</td>
	<td>0.6999879</td>
	<td>0.1130667</td>
	<td>0.6284978</td>
	<td>1.2690362</td>
	<td>0.1168635</td>
	<td>0.2359657</td>
	<td>0.0628460</td>
	<td>0.8883100</td>
	<td>-37.1502161</td>
	<td>26.9036234</td></tr>
	<tr><td></td>
	<td>14</td>
	<td>0.7999818</td>
	<td>0.0982229</td>
	<td>0.5259192</td>
	<td>1.1761501</td>
	<td>0.0977899</td>
	<td>0.2186944</td>
	<td>0.0525887</td>
	<td>0.9408987</td>
	<td>-47.4080824</td>
	<td>17.6150117</td></tr>
	<tr><td></td>
	<td>15</td>
	<td>0.8999758</td>
	<td>0.0826149</td>
	<td>0.3989170</td>
	<td>1.0897938</td>
	<td>0.0741750</td>
	<td>0.2026372</td>
	<td>0.0398893</td>
	<td>0.9807880</td>
	<td>-60.1082978</td>
	<td>8.9793790</td></tr>
	<tr><td></td>
	<td>16</td>
	<td>1.0</td>
	<td>0.0605773</td>
	<td>0.1920733</td>
	<td>1.0</td>
	<td>0.0357143</td>
	<td>0.1859409</td>
	<td>0.0192120</td>
	<td>1.0</td>
	<td>-80.7926687</td>
	<td>0.0</td></tr></table></div>
	</div>

	</div>

	<div class="output_area">
	<div class="prompt"></div>

	<div class="output_subarea output_stream output_stdout output_text">
	<pre>

	ModelMetricsBinomialGLM: stackedensemble
	Reported on cross-validation data.

	MSE: 0.1369765435568584
	RMSE: 0.3701034227845757
	LogLoss: 0.4355309009590542
	Null degrees of freedom: 130954
	Residual degrees of freedom: 130943
	Null deviance: 124375.46514588114
	Residual deviance: 114069.89827018589
	AIC: 114093.89827018589
	AUC: 0.7071203432205223
	Gini: 0.4142406864410446
	Confusion Matrix (Act/Pred) for max f1 @ threshold = 0.17843972441369682:
	</pre>
	</div>
	</div>

	<div class="output_area">
	<div class="prompt"></div>


	<div class="output_html rendered_html output_subarea ">
	<div style="overflow:auto"><table style="width:50%"><tr><td><b></b></td>
	<td><b>0</b></td>
	<td><b>1</b></td>
	<td><b>Error</b></td>
	<td><b>Rate</b></td></tr>
	<tr><td>0</td>
	<td>73561.0</td>
	<td>33520.0</td>
	<td>0.313</td>
	<td> (33520.0/107081.0)</td></tr>
	<tr><td>1</td>
	<td>9215.0</td>
	<td>14659.0</td>
	<td>0.386</td>
	<td> (9215.0/23874.0)</td></tr>
	<tr><td>Total</td>
	<td>82776.0</td>
	<td>48179.0</td>
	<td>0.3263</td>
	<td> (42735.0/130955.0)</td></tr></table></div>
	</div>

	</div>

	<div class="output_area">
	<div class="prompt"></div>

	<div class="output_subarea output_stream output_stdout output_text">
	<pre>Maximum Metrics: Maximum metrics at their respective thresholds

	</pre>
	</div>
	</div>

	<div class="output_area">
	<div class="prompt"></div>


	<div class="output_html rendered_html output_subarea ">
	<div style="overflow:auto"><table style="width:50%"><tr><td><b>metric</b></td>
	<td><b>threshold</b></td>
	<td><b>value</b></td>
	<td><b>idx</b></td></tr>
	<tr><td>max f1</td>
	<td>0.1784397</td>
	<td>0.4068949</td>
	<td>261.0</td></tr>
	<tr><td>max f2</td>
	<td>0.1136746</td>
	<td>0.5665672</td>
	<td>334.0</td></tr>
	<tr><td>max f0point5</td>
	<td>0.2879939</td>
	<td>0.3708050</td>
	<td>176.0</td></tr>
	<tr><td>max accuracy</td>
	<td>0.5663591</td>
	<td>0.8184567</td>
	<td>36.0</td></tr>
	<tr><td>max precision</td>
	<td>0.7859236</td>
	<td>1.0</td>
	<td>0.0</td></tr>
	<tr><td>max recall</td>
	<td>0.0620870</td>
	<td>1.0</td>
	<td>399.0</td></tr>
	<tr><td>max specificity</td>
	<td>0.7859236</td>
	<td>1.0</td>
	<td>0.0</td></tr>
	<tr><td>max absolute_mcc</td>
	<td>0.1815977</td>
	<td>0.2412252</td>
	<td>258.0</td></tr>
	<tr><td>max min_per_class_accuracy</td>
	<td>0.1671726</td>
	<td>0.6498819</td>
	<td>272.0</td></tr>
	<tr><td>max mean_per_class_accuracy</td>
	<td>0.1616542</td>
	<td>0.6512829</td>
	<td>278.0</td></tr></table></div>
	</div>

	</div>

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	<div class="output_subarea output_stream output_stdout output_text">
	<pre>Gains/Lift Table: Avg response rate: 18.23 %

	</pre>
	</div>
	</div>

	<div class="output_area">
	<div class="prompt"></div>


	<div class="output_html rendered_html output_subarea ">
	<div style="overflow:auto"><table style="width:50%"><tr><td><b></b></td>
	<td><b>group</b></td>
	<td><b>cumulative_data_fraction</b></td>
	<td><b>lower_threshold</b></td>
	<td><b>lift</b></td>
	<td><b>cumulative_lift</b></td>
	<td><b>response_rate</b></td>
	<td><b>cumulative_response_rate</b></td>
	<td><b>capture_rate</b></td>
	<td><b>cumulative_capture_rate</b></td>
	<td><b>gain</b></td>
	<td><b>cumulative_gain</b></td></tr>
	<tr><td></td>
	<td>1</td>
	<td>0.0100034</td>
	<td>0.5609815</td>
	<td>2.9394272</td>
	<td>2.9394272</td>
	<td>0.5358779</td>
	<td>0.5358779</td>
	<td>0.0294044</td>
	<td>0.0294044</td>
	<td>193.9427222</td>
	<td>193.9427222</td></tr>
	<tr><td></td>
	<td>2</td>
	<td>0.0200069</td>
	<td>0.5136764</td>
	<td>2.6044498</td>
	<td>2.7719385</td>
	<td>0.4748092</td>
	<td>0.5053435</td>
	<td>0.0260534</td>
	<td>0.0554578</td>
	<td>160.4449761</td>
	<td>177.1938491</td></tr>
	<tr><td></td>
	<td>3</td>
	<td>0.0300027</td>
	<td>0.4802174</td>
	<td>2.4346323</td>
	<td>2.6595603</td>
	<td>0.4438503</td>
	<td>0.4848562</td>
	<td>0.0243361</td>
	<td>0.0797939</td>
	<td>143.4632310</td>
	<td>165.9560331</td></tr>
	<tr><td></td>
	<td>4</td>
	<td>0.0400061</td>
	<td>0.4541967</td>
	<td>2.2987828</td>
	<td>2.5693487</td>
	<td>0.4190840</td>
	<td>0.4684100</td>
	<td>0.0229957</td>
	<td>0.1027896</td>
	<td>129.8782827</td>
	<td>156.9348739</td></tr>
	<tr><td></td>
	<td>5</td>
	<td>0.0500019</td>
	<td>0.4304407</td>
	<td>2.3592048</td>
	<td>2.5273392</td>
	<td>0.4300993</td>
	<td>0.4607514</td>
	<td>0.0235821</td>
	<td>0.1263718</td>
	<td>135.9204803</td>
	<td>152.7339208</td></tr>
	<tr><td></td>
	<td>6</td>
	<td>0.1000038</td>
	<td>0.3489922</td>
	<td>2.0674422</td>
	<td>2.2973907</td>
	<td>0.3769090</td>
	<td>0.4188302</td>
	<td>0.1033761</td>
	<td>0.2297478</td>
	<td>106.7442216</td>
	<td>129.7390712</td></tr>
	<tr><td></td>
	<td>7</td>
	<td>0.1500057</td>
	<td>0.2957391</td>
	<td>1.7583311</td>
	<td>2.1177042</td>
	<td>0.3205559</td>
	<td>0.3860721</td>
	<td>0.0879199</td>
	<td>0.3176678</td>
	<td>75.8331123</td>
	<td>111.7704182</td></tr>
	<tr><td></td>
	<td>8</td>
	<td>0.2</td>
	<td>0.2569097</td>
	<td>1.5826559</td>
	<td>1.9839574</td>
	<td>0.2885291</td>
	<td>0.3616891</td>
	<td>0.0791237</td>
	<td>0.3967915</td>
	<td>58.2655941</td>
	<td>98.3957443</td></tr>
	<tr><td></td>
	<td>9</td>
	<td>0.3000038</td>
	<td>0.2032167</td>
	<td>1.3679632</td>
	<td>1.7786208</td>
	<td>0.2493891</td>
	<td>0.3242548</td>
	<td>0.1368015</td>
	<td>0.5335930</td>
	<td>36.7963184</td>
	<td>77.8620797</td></tr>
	<tr><td></td>
	<td>10</td>
	<td>0.4</td>
	<td>0.1679941</td>
	<td>1.1284673</td>
	<td>1.6160886</td>
	<td>0.2057274</td>
	<td>0.2946241</td>
	<td>0.1128424</td>
	<td>0.6464355</td>
	<td>12.8467313</td>
	<td>61.6088632</td></tr>
	<tr><td></td>
	<td>11</td>
	<td>0.5000038</td>
	<td>0.1428590</td>
	<td>0.9302652</td>
	<td>1.4789198</td>
	<td>0.1695938</td>
	<td>0.2696173</td>
	<td>0.0930301</td>
	<td>0.7394655</td>
	<td>-6.9734773</td>
	<td>47.8919761</td></tr>
	<tr><td></td>
	<td>12</td>
	<td>0.6</td>
	<td>0.1238863</td>
	<td>0.8143060</td>
	<td>1.3681550</td>
	<td>0.1484536</td>
	<td>0.2494241</td>
	<td>0.0814275</td>
	<td>0.8208930</td>
	<td>-18.5693965</td>
	<td>36.8155036</td></tr>
	<tr><td></td>
	<td>13</td>
	<td>0.6999962</td>
	<td>0.1081113</td>
	<td>0.6589009</td>
	<td>1.2668363</td>
	<td>0.1201222</td>
	<td>0.2309530</td>
	<td>0.0658876</td>
	<td>0.8867806</td>
	<td>-34.1099078</td>
	<td>26.6836336</td></tr>
	<tr><td></td>
	<td>14</td>
	<td>0.8</td>
	<td>0.0941428</td>
	<td>0.5185360</td>
	<td>1.1732952</td>
	<td>0.0945327</td>
	<td>0.2138998</td>
	<td>0.0518556</td>
	<td>0.9386362</td>
	<td>-48.1464047</td>
	<td>17.3295217</td></tr>
	<tr><td></td>
	<td>15</td>
	<td>0.8999962</td>
	<td>0.0801775</td>
	<td>0.3945866</td>
	<td>1.0867750</td>
	<td>0.0719359</td>
	<td>0.1981266</td>
	<td>0.0394572</td>
	<td>0.9780933</td>
	<td>-60.5413434</td>
	<td>8.6774970</td></tr>
	<tr><td></td>
	<td>16</td>
	<td>1.0</td>
	<td>0.0597666</td>
	<td>0.2190584</td>
	<td>1.0</td>
	<td>0.0399359</td>
	<td>0.1823069</td>
	<td>0.0219067</td>
	<td>1.0</td>
	<td>-78.0941597</td>
	<td>0.0</td></tr></table></div>
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	<pre><bound method H2OBinomialModel.tpr of ></pre>
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	<div class=" highlight hl-ipython3"><pre><span></span><span class="n">aml</span><span class="o">.</span><span class="n">leader</span><span class="o">.</span><span class="n">weights</span>
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	<pre>Model Details
	=============
	H2OStackedEnsembleEstimator : Stacked Ensemble
	Model Key: StackedEnsemble_AllModels_0_AutoML_20181120_154205
	No model summary for this model


	ModelMetricsBinomialGLM: stackedensemble
	Reported on train data.

	MSE: 0.12685990330985406
	RMSE: 0.3561739789904002
	LogLoss: 0.40703958453227496
	Null degrees of freedom: 130954
	Residual degrees of freedom: 130943
	Null deviance: 124374.13927893189
	Residual deviance: 106607.73758484815
	AIC: 106631.73758484815
	AUC: 0.7734040182726795
	Gini: 0.5468080365453589
	Confusion Matrix (Act/Pred) for max f1 @ threshold = 0.21708051286464972:
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	<td><b>0</b></td>
	<td><b>1</b></td>
	<td><b>Error</b></td>
	<td><b>Rate</b></td></tr>
	<tr><td>0</td>
	<td>83212.0</td>
	<td>23869.0</td>
	<td>0.2229</td>
	<td> (23869.0/107081.0)</td></tr>
	<tr><td>1</td>
	<td>9376.0</td>
	<td>14498.0</td>
	<td>0.3927</td>
	<td> (9376.0/23874.0)</td></tr>
	<tr><td>Total</td>
	<td>92588.0</td>
	<td>38367.0</td>
	<td>0.2539</td>
	<td> (33245.0/130955.0)</td></tr></table></div>
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	<pre>Maximum Metrics: Maximum metrics at their respective thresholds

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	<div style="overflow:auto"><table style="width:50%"><tr><td><b>metric</b></td>
	<td><b>threshold</b></td>
	<td><b>value</b></td>
	<td><b>idx</b></td></tr>
	<tr><td>max f1</td>
	<td>0.2170805</td>
	<td>0.4658666</td>
	<td>238.0</td></tr>
	<tr><td>max f2</td>
	<td>0.1410190</td>
	<td>0.6067433</td>
	<td>309.0</td></tr>
	<tr><td>max f0point5</td>
	<td>0.3338429</td>
	<td>0.4568693</td>
	<td>155.0</td></tr>
	<tr><td>max accuracy</td>
	<td>0.4390853</td>
	<td>0.8290100</td>
	<td>98.0</td></tr>
	<tr><td>max precision</td>
	<td>0.8006766</td>
	<td>1.0</td>
	<td>0.0</td></tr>
	<tr><td>max recall</td>
	<td>0.0676438</td>
	<td>1.0</td>
	<td>394.0</td></tr>
	<tr><td>max specificity</td>
	<td>0.8006766</td>
	<td>1.0</td>
	<td>0.0</td></tr>
	<tr><td>max absolute_mcc</td>
	<td>0.2335835</td>
	<td>0.3269004</td>
	<td>224.0</td></tr>
	<tr><td>max min_per_class_accuracy</td>
	<td>0.1855661</td>
	<td>0.6993958</td>
	<td>265.0</td></tr>
	<tr><td>max mean_per_class_accuracy</td>
	<td>0.1761337</td>
	<td>0.7006208</td>
	<td>274.0</td></tr></table></div>
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	<pre>Gains/Lift Table: Avg response rate: 18.23 %

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	<div style="overflow:auto"><table style="width:50%"><tr><td><b></b></td>
	<td><b>group</b></td>
	<td><b>cumulative_data_fraction</b></td>
	<td><b>lower_threshold</b></td>
	<td><b>lift</b></td>
	<td><b>cumulative_lift</b></td>
	<td><b>response_rate</b></td>
	<td><b>cumulative_response_rate</b></td>
	<td><b>capture_rate</b></td>
	<td><b>cumulative_capture_rate</b></td>
	<td><b>gain</b></td>
	<td><b>cumulative_gain</b></td></tr>
	<tr><td></td>
	<td>1</td>
	<td>0.0100034</td>
	<td>0.5809896</td>
	<td>4.2290904</td>
	<td>4.2290904</td>
	<td>0.7709924</td>
	<td>0.7709924</td>
	<td>0.0423054</td>
	<td>0.0423054</td>
	<td>322.9090447</td>
	<td>322.9090447</td></tr>
	<tr><td></td>
	<td>2</td>
	<td>0.0200069</td>
	<td>0.5350310</td>
	<td>3.4879528</td>
	<td>3.8585216</td>
	<td>0.6358779</td>
	<td>0.7034351</td>
	<td>0.0348915</td>
	<td>0.0771970</td>
	<td>248.7952815</td>
	<td>285.8521631</td></tr>
	<tr><td></td>
	<td>3</td>
	<td>0.0300027</td>
	<td>0.5007744</td>
	<td>3.1972882</td>
	<td>3.6382227</td>
	<td>0.5828877</td>
	<td>0.6632731</td>
	<td>0.0319595</td>
	<td>0.1091564</td>
	<td>219.7288214</td>
	<td>263.8222689</td></tr>
	<tr><td></td>
	<td>4</td>
	<td>0.0400061</td>
	<td>0.4718430</td>
	<td>2.9436144</td>
	<td>3.4645375</td>
	<td>0.5366412</td>
	<td>0.6316091</td>
	<td>0.0294463</td>
	<td>0.1386027</td>
	<td>194.3614440</td>
	<td>246.4537481</td></tr>
	<tr><td></td>
	<td>5</td>
	<td>0.0500019</td>
	<td>0.4483865</td>
	<td>2.8704357</td>
	<td>3.3457716</td>
	<td>0.5233002</td>
	<td>0.6099572</td>
	<td>0.0286923</td>
	<td>0.1672950</td>
	<td>187.0435684</td>
	<td>234.5771560</td></tr>
	<tr><td></td>
	<td>6</td>
	<td>0.1000038</td>
	<td>0.3623038</td>
	<td>2.4444070</td>
	<td>2.8950893</td>
	<td>0.4456323</td>
	<td>0.5277947</td>
	<td>0.1222250</td>
	<td>0.2895200</td>
	<td>144.4406963</td>
	<td>189.5089261</td></tr>
	<tr><td></td>
	<td>7</td>
	<td>0.1500057</td>
	<td>0.3079302</td>
	<td>1.9878608</td>
	<td>2.5926798</td>
	<td>0.3624007</td>
	<td>0.4726634</td>
	<td>0.0993968</td>
	<td>0.3889168</td>
	<td>98.7860769</td>
	<td>159.2679764</td></tr>
	<tr><td></td>
	<td>8</td>
	<td>0.2</td>
	<td>0.2684456</td>
	<td>1.7116814</td>
	<td>2.3724554</td>
	<td>0.3120513</td>
	<td>0.4325150</td>
	<td>0.0855743</td>
	<td>0.4744911</td>
	<td>71.1681359</td>
	<td>137.2455391</td></tr>
	<tr><td></td>
	<td>9</td>
	<td>0.3000038</td>
	<td>0.2132009</td>
	<td>1.4102670</td>
	<td>2.0517178</td>
	<td>0.2571014</td>
	<td>0.3740423</td>
	<td>0.1410321</td>
	<td>0.6155232</td>
	<td>41.0267006</td>
	<td>105.1717765</td></tr>
	<tr><td></td>
	<td>10</td>
	<td>0.4</td>
	<td>0.1765625</td>
	<td>1.1217652</td>
	<td>1.8192385</td>
	<td>0.2045055</td>
	<td>0.3316597</td>
	<td>0.1121722</td>
	<td>0.7276954</td>
	<td>12.1765206</td>
	<td>81.9238502</td></tr>
	<tr><td></td>
	<td>11</td>
	<td>0.5000038</td>
	<td>0.1503145</td>
	<td>0.8745582</td>
	<td>1.6302967</td>
	<td>0.1594380</td>
	<td>0.2972143</td>
	<td>0.0874592</td>
	<td>0.8151546</td>
	<td>-12.5441786</td>
	<td>63.0296674</td></tr>
	<tr><td></td>
	<td>12</td>
	<td>0.6</td>
	<td>0.1300345</td>
	<td>0.6769128</td>
	<td>1.4714054</td>
	<td>0.1234059</td>
	<td>0.2682474</td>
	<td>0.0676887</td>
	<td>0.8828433</td>
	<td>-32.3087165</td>
	<td>47.1405434</td></tr>
	<tr><td></td>
	<td>13</td>
	<td>0.6999962</td>
	<td>0.1129563</td>
	<td>0.4959559</td>
	<td>1.3320601</td>
	<td>0.0904162</td>
	<td>0.2428437</td>
	<td>0.0495937</td>
	<td>0.9324370</td>
	<td>-50.4044061</td>
	<td>33.2060067</td></tr>
	<tr><td></td>
	<td>14</td>
	<td>0.8</td>
	<td>0.0978849</td>
	<td>0.3920433</td>
	<td>1.2145535</td>
	<td>0.0714722</td>
	<td>0.2214215</td>
	<td>0.0392058</td>
	<td>0.9716428</td>
	<td>-60.7956663</td>
	<td>21.4553489</td></tr>
	<tr><td></td>
	<td>15</td>
	<td>0.8999962</td>
	<td>0.0824531</td>
	<td>0.2194940</td>
	<td>1.1039951</td>
	<td>0.0400153</td>
	<td>0.2012659</td>
	<td>0.0219486</td>
	<td>0.9935914</td>
	<td>-78.0505987</td>
	<td>10.3995078</td></tr>
	<tr><td></td>
	<td>16</td>
	<td>1.0</td>
	<td>0.0597755</td>
	<td>0.0640840</td>
	<td>1.0</td>
	<td>0.0116830</td>
	<td>0.1823069</td>
	<td>0.0064086</td>
	<td>1.0</td>
	<td>-93.5915993</td>
	<td>0.0</td></tr></table></div>
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	<pre>

	ModelMetricsBinomialGLM: stackedensemble
	Reported on validation data.

	MSE: 0.13813682407268132
	RMSE: 0.37166762580655494
	LogLoss: 0.4379927029517987
	Null degrees of freedom: 33031
	Residual degrees of freedom: 33020
	Null deviance: 31732.354674481932
	Residual deviance: 28935.54992780763
	AIC: 28959.54992780763
	AUC: 0.7122628231156057
	Gini: 0.4245256462312115
	Confusion Matrix (Act/Pred) for max f1 @ threshold = 0.18933454821029921:
	</pre>
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	<div style="overflow:auto"><table style="width:50%"><tr><td><b></b></td>
	<td><b>0</b></td>
	<td><b>1</b></td>
	<td><b>Error</b></td>
	<td><b>Rate</b></td></tr>
	<tr><td>0</td>
	<td>18652.0</td>
	<td>8238.0</td>
	<td>0.3064</td>
	<td> (8238.0/26890.0)</td></tr>
	<tr><td>1</td>
	<td>2386.0</td>
	<td>3756.0</td>
	<td>0.3885</td>
	<td> (2386.0/6142.0)</td></tr>
	<tr><td>Total</td>
	<td>21038.0</td>
	<td>11994.0</td>
	<td>0.3216</td>
	<td> (10624.0/33032.0)</td></tr></table></div>
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	<pre>Maximum Metrics: Maximum metrics at their respective thresholds

	</pre>
	</div>
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	<div class="output_area">
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	<div style="overflow:auto"><table style="width:50%"><tr><td><b>metric</b></td>
	<td><b>threshold</b></td>
	<td><b>value</b></td>
	<td><b>idx</b></td></tr>
	<tr><td>max f1</td>
	<td>0.1893345</td>
	<td>0.4142038</td>
	<td>256.0</td></tr>
	<tr><td>max f2</td>
	<td>0.1197407</td>
	<td>0.5738535</td>
	<td>330.0</td></tr>
	<tr><td>max f0point5</td>
	<td>0.3129965</td>
	<td>0.3817812</td>
	<td>160.0</td></tr>
	<tr><td>max accuracy</td>
	<td>0.6010242</td>
	<td>0.8160572</td>
	<td>29.0</td></tr>
	<tr><td>max precision</td>
	<td>0.7666583</td>
	<td>1.0</td>
	<td>0.0</td></tr>
	<tr><td>max recall</td>
	<td>0.0640080</td>
	<td>1.0</td>
	<td>398.0</td></tr>
	<tr><td>max specificity</td>
	<td>0.7666583</td>
	<td>1.0</td>
	<td>0.0</td></tr>
	<tr><td>max absolute_mcc</td>
	<td>0.2092723</td>
	<td>0.2475688</td>
	<td>238.0</td></tr>
	<tr><td>max min_per_class_accuracy</td>
	<td>0.1762849</td>
	<td>0.6525562</td>
	<td>268.0</td></tr>
	<tr><td>max mean_per_class_accuracy</td>
	<td>0.1577331</td>
	<td>0.6547886</td>
	<td>286.0</td></tr></table></div>
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	<pre>Gains/Lift Table: Avg response rate: 18.59 %

	</pre>
	</div>
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	<div style="overflow:auto"><table style="width:50%"><tr><td><b></b></td>
	<td><b>group</b></td>
	<td><b>cumulative_data_fraction</b></td>
	<td><b>lower_threshold</b></td>
	<td><b>lift</b></td>
	<td><b>cumulative_lift</b></td>
	<td><b>response_rate</b></td>
	<td><b>cumulative_response_rate</b></td>
	<td><b>capture_rate</b></td>
	<td><b>cumulative_capture_rate</b></td>
	<td><b>gain</b></td>
	<td><b>cumulative_gain</b></td></tr>
	<tr><td></td>
	<td>1</td>
	<td>0.0100206</td>
	<td>0.5783690</td>
	<td>3.1358434</td>
	<td>3.1358434</td>
	<td>0.5830816</td>
	<td>0.5830816</td>
	<td>0.0314230</td>
	<td>0.0314230</td>
	<td>213.5843447</td>
	<td>213.5843447</td></tr>
	<tr><td></td>
	<td>2</td>
	<td>0.0200109</td>
	<td>0.5293169</td>
	<td>2.5749465</td>
	<td>2.8558192</td>
	<td>0.4787879</td>
	<td>0.5310136</td>
	<td>0.0257245</td>
	<td>0.0571475</td>
	<td>157.4946469</td>
	<td>185.5819237</td></tr>
	<tr><td></td>
	<td>3</td>
	<td>0.0300012</td>
	<td>0.4955180</td>
	<td>2.4119752</td>
	<td>2.7080205</td>
	<td>0.4484848</td>
	<td>0.5035318</td>
	<td>0.0240964</td>
	<td>0.0812439</td>
	<td>141.1975173</td>
	<td>170.8020508</td></tr>
	<tr><td></td>
	<td>4</td>
	<td>0.0400218</td>
	<td>0.4688250</td>
	<td>2.4859277</td>
	<td>2.6524133</td>
	<td>0.4622356</td>
	<td>0.4931921</td>
	<td>0.0249105</td>
	<td>0.1061543</td>
	<td>148.5927707</td>
	<td>165.2413309</td></tr>
	<tr><td></td>
	<td>5</td>
	<td>0.0500121</td>
	<td>0.4455599</td>
	<td>2.2164096</td>
	<td>2.5653181</td>
	<td>0.4121212</td>
	<td>0.4769976</td>
	<td>0.0221426</td>
	<td>0.1282970</td>
	<td>121.6409619</td>
	<td>156.5318141</td></tr>
	<tr><td></td>
	<td>6</td>
	<td>0.1000242</td>
	<td>0.3612868</td>
	<td>2.0607188</td>
	<td>2.3130185</td>
	<td>0.3831719</td>
	<td>0.4300847</td>
	<td>0.1030609</td>
	<td>0.2313579</td>
	<td>106.0718760</td>
	<td>131.3018450</td></tr>
	<tr><td></td>
	<td>7</td>
	<td>0.1500061</td>
	<td>0.3068785</td>
	<td>1.7850835</td>
	<td>2.1371112</td>
	<td>0.3319200</td>
	<td>0.3973764</td>
	<td>0.0892218</td>
	<td>0.3205796</td>
	<td>78.5083530</td>
	<td>113.7111174</td></tr>
	<tr><td></td>
	<td>8</td>
	<td>0.2000182</td>
	<td>0.2675737</td>
	<td>1.5756523</td>
	<td>1.9967252</td>
	<td>0.2929782</td>
	<td>0.3712729</td>
	<td>0.0788017</td>
	<td>0.3993813</td>
	<td>57.5652259</td>
	<td>99.6725200</td></tr>
	<tr><td></td>
	<td>9</td>
	<td>0.3000121</td>
	<td>0.2132448</td>
	<td>1.3758567</td>
	<td>1.7897899</td>
	<td>0.2558280</td>
	<td>0.3327952</td>
	<td>0.1375773</td>
	<td>0.5369586</td>
	<td>37.5856668</td>
	<td>78.9789907</td></tr>
	<tr><td></td>
	<td>10</td>
	<td>0.4000061</td>
	<td>0.1764937</td>
	<td>1.1299935</td>
	<td>1.6248533</td>
	<td>0.2101120</td>
	<td>0.3021267</td>
	<td>0.1129925</td>
	<td>0.6499512</td>
	<td>12.9993524</td>
	<td>62.4853295</td></tr>
	<tr><td></td>
	<td>11</td>
	<td>0.5</td>
	<td>0.1497263</td>
	<td>0.9964784</td>
	<td>1.4991859</td>
	<td>0.1852861</td>
	<td>0.2787600</td>
	<td>0.0996418</td>
	<td>0.7495930</td>
	<td>-0.3521561</td>
	<td>49.9185933</td></tr>
	<tr><td></td>
	<td>12</td>
	<td>0.5999939</td>
	<td>0.1296393</td>
	<td>0.7587565</td>
	<td>1.3757872</td>
	<td>0.1410839</td>
	<td>0.2558151</td>
	<td>0.0758711</td>
	<td>0.8254640</td>
	<td>-24.1243542</td>
	<td>37.5787247</td></tr>
	<tr><td></td>
	<td>13</td>
	<td>0.6999879</td>
	<td>0.1130667</td>
	<td>0.6284978</td>
	<td>1.2690362</td>
	<td>0.1168635</td>
	<td>0.2359657</td>
	<td>0.0628460</td>
	<td>0.8883100</td>
	<td>-37.1502161</td>
	<td>26.9036234</td></tr>
	<tr><td></td>
	<td>14</td>
	<td>0.7999818</td>
	<td>0.0982229</td>
	<td>0.5259192</td>
	<td>1.1761501</td>
	<td>0.0977899</td>
	<td>0.2186944</td>
	<td>0.0525887</td>
	<td>0.9408987</td>
	<td>-47.4080824</td>
	<td>17.6150117</td></tr>
	<tr><td></td>
	<td>15</td>
	<td>0.8999758</td>
	<td>0.0826149</td>
	<td>0.3989170</td>
	<td>1.0897938</td>
	<td>0.0741750</td>
	<td>0.2026372</td>
	<td>0.0398893</td>
	<td>0.9807880</td>
	<td>-60.1082978</td>
	<td>8.9793790</td></tr>
	<tr><td></td>
	<td>16</td>
	<td>1.0</td>
	<td>0.0605773</td>
	<td>0.1920733</td>
	<td>1.0</td>
	<td>0.0357143</td>
	<td>0.1859409</td>
	<td>0.0192120</td>
	<td>1.0</td>
	<td>-80.7926687</td>
	<td>0.0</td></tr></table></div>
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	<pre>

	ModelMetricsBinomialGLM: stackedensemble
	Reported on cross-validation data.

	MSE: 0.1369765435568584
	RMSE: 0.3701034227845757
	LogLoss: 0.4355309009590542
	Null degrees of freedom: 130954
	Residual degrees of freedom: 130943
	Null deviance: 124375.46514588114
	Residual deviance: 114069.89827018589
	AIC: 114093.89827018589
	AUC: 0.7071203432205223
	Gini: 0.4142406864410446
	Confusion Matrix (Act/Pred) for max f1 @ threshold = 0.17843972441369682:
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	<div style="overflow:auto"><table style="width:50%"><tr><td><b></b></td>
	<td><b>0</b></td>
	<td><b>1</b></td>
	<td><b>Error</b></td>
	<td><b>Rate</b></td></tr>
	<tr><td>0</td>
	<td>73561.0</td>
	<td>33520.0</td>
	<td>0.313</td>
	<td> (33520.0/107081.0)</td></tr>
	<tr><td>1</td>
	<td>9215.0</td>
	<td>14659.0</td>
	<td>0.386</td>
	<td> (9215.0/23874.0)</td></tr>
	<tr><td>Total</td>
	<td>82776.0</td>
	<td>48179.0</td>
	<td>0.3263</td>
	<td> (42735.0/130955.0)</td></tr></table></div>
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	<pre>Maximum Metrics: Maximum metrics at their respective thresholds

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	<div style="overflow:auto"><table style="width:50%"><tr><td><b>metric</b></td>
	<td><b>threshold</b></td>
	<td><b>value</b></td>
	<td><b>idx</b></td></tr>
	<tr><td>max f1</td>
	<td>0.1784397</td>
	<td>0.4068949</td>
	<td>261.0</td></tr>
	<tr><td>max f2</td>
	<td>0.1136746</td>
	<td>0.5665672</td>
	<td>334.0</td></tr>
	<tr><td>max f0point5</td>
	<td>0.2879939</td>
	<td>0.3708050</td>
	<td>176.0</td></tr>
	<tr><td>max accuracy</td>
	<td>0.5663591</td>
	<td>0.8184567</td>
	<td>36.0</td></tr>
	<tr><td>max precision</td>
	<td>0.7859236</td>
	<td>1.0</td>
	<td>0.0</td></tr>
	<tr><td>max recall</td>
	<td>0.0620870</td>
	<td>1.0</td>
	<td>399.0</td></tr>
	<tr><td>max specificity</td>
	<td>0.7859236</td>
	<td>1.0</td>
	<td>0.0</td></tr>
	<tr><td>max absolute_mcc</td>
	<td>0.1815977</td>
	<td>0.2412252</td>
	<td>258.0</td></tr>
	<tr><td>max min_per_class_accuracy</td>
	<td>0.1671726</td>
	<td>0.6498819</td>
	<td>272.0</td></tr>
	<tr><td>max mean_per_class_accuracy</td>
	<td>0.1616542</td>
	<td>0.6512829</td>
	<td>278.0</td></tr></table></div>
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	<pre>Gains/Lift Table: Avg response rate: 18.23 %

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	<div style="overflow:auto"><table style="width:50%"><tr><td><b></b></td>
	<td><b>group</b></td>
	<td><b>cumulative_data_fraction</b></td>
	<td><b>lower_threshold</b></td>
	<td><b>lift</b></td>
	<td><b>cumulative_lift</b></td>
	<td><b>response_rate</b></td>
	<td><b>cumulative_response_rate</b></td>
	<td><b>capture_rate</b></td>
	<td><b>cumulative_capture_rate</b></td>
	<td><b>gain</b></td>
	<td><b>cumulative_gain</b></td></tr>
	<tr><td></td>
	<td>1</td>
	<td>0.0100034</td>
	<td>0.5609815</td>
	<td>2.9394272</td>
	<td>2.9394272</td>
	<td>0.5358779</td>
	<td>0.5358779</td>
	<td>0.0294044</td>
	<td>0.0294044</td>
	<td>193.9427222</td>
	<td>193.9427222</td></tr>
	<tr><td></td>
	<td>2</td>
	<td>0.0200069</td>
	<td>0.5136764</td>
	<td>2.6044498</td>
	<td>2.7719385</td>
	<td>0.4748092</td>
	<td>0.5053435</td>
	<td>0.0260534</td>
	<td>0.0554578</td>
	<td>160.4449761</td>
	<td>177.1938491</td></tr>
	<tr><td></td>
	<td>3</td>
	<td>0.0300027</td>
	<td>0.4802174</td>
	<td>2.4346323</td>
	<td>2.6595603</td>
	<td>0.4438503</td>
	<td>0.4848562</td>
	<td>0.0243361</td>
	<td>0.0797939</td>
	<td>143.4632310</td>
	<td>165.9560331</td></tr>
	<tr><td></td>
	<td>4</td>
	<td>0.0400061</td>
	<td>0.4541967</td>
	<td>2.2987828</td>
	<td>2.5693487</td>
	<td>0.4190840</td>
	<td>0.4684100</td>
	<td>0.0229957</td>
	<td>0.1027896</td>
	<td>129.8782827</td>
	<td>156.9348739</td></tr>
	<tr><td></td>
	<td>5</td>
	<td>0.0500019</td>
	<td>0.4304407</td>
	<td>2.3592048</td>
	<td>2.5273392</td>
	<td>0.4300993</td>
	<td>0.4607514</td>
	<td>0.0235821</td>
	<td>0.1263718</td>
	<td>135.9204803</td>
	<td>152.7339208</td></tr>
	<tr><td></td>
	<td>6</td>
	<td>0.1000038</td>
	<td>0.3489922</td>
	<td>2.0674422</td>
	<td>2.2973907</td>
	<td>0.3769090</td>
	<td>0.4188302</td>
	<td>0.1033761</td>
	<td>0.2297478</td>
	<td>106.7442216</td>
	<td>129.7390712</td></tr>
	<tr><td></td>
	<td>7</td>
	<td>0.1500057</td>
	<td>0.2957391</td>
	<td>1.7583311</td>
	<td>2.1177042</td>
	<td>0.3205559</td>
	<td>0.3860721</td>
	<td>0.0879199</td>
	<td>0.3176678</td>
	<td>75.8331123</td>
	<td>111.7704182</td></tr>
	<tr><td></td>
	<td>8</td>
	<td>0.2</td>
	<td>0.2569097</td>
	<td>1.5826559</td>
	<td>1.9839574</td>
	<td>0.2885291</td>
	<td>0.3616891</td>
	<td>0.0791237</td>
	<td>0.3967915</td>
	<td>58.2655941</td>
	<td>98.3957443</td></tr>
	<tr><td></td>
	<td>9</td>
	<td>0.3000038</td>
	<td>0.2032167</td>
	<td>1.3679632</td>
	<td>1.7786208</td>
	<td>0.2493891</td>
	<td>0.3242548</td>
	<td>0.1368015</td>
	<td>0.5335930</td>
	<td>36.7963184</td>
	<td>77.8620797</td></tr>
	<tr><td></td>
	<td>10</td>
	<td>0.4</td>
	<td>0.1679941</td>
	<td>1.1284673</td>
	<td>1.6160886</td>
	<td>0.2057274</td>
	<td>0.2946241</td>
	<td>0.1128424</td>
	<td>0.6464355</td>
	<td>12.8467313</td>
	<td>61.6088632</td></tr>
	<tr><td></td>
	<td>11</td>
	<td>0.5000038</td>
	<td>0.1428590</td>
	<td>0.9302652</td>
	<td>1.4789198</td>
	<td>0.1695938</td>
	<td>0.2696173</td>
	<td>0.0930301</td>
	<td>0.7394655</td>
	<td>-6.9734773</td>
	<td>47.8919761</td></tr>
	<tr><td></td>
	<td>12</td>
	<td>0.6</td>
	<td>0.1238863</td>
	<td>0.8143060</td>
	<td>1.3681550</td>
	<td>0.1484536</td>
	<td>0.2494241</td>
	<td>0.0814275</td>
	<td>0.8208930</td>
	<td>-18.5693965</td>
	<td>36.8155036</td></tr>
	<tr><td></td>
	<td>13</td>
	<td>0.6999962</td>
	<td>0.1081113</td>
	<td>0.6589009</td>
	<td>1.2668363</td>
	<td>0.1201222</td>
	<td>0.2309530</td>
	<td>0.0658876</td>
	<td>0.8867806</td>
	<td>-34.1099078</td>
	<td>26.6836336</td></tr>
	<tr><td></td>
	<td>14</td>
	<td>0.8</td>
	<td>0.0941428</td>
	<td>0.5185360</td>
	<td>1.1732952</td>
	<td>0.0945327</td>
	<td>0.2138998</td>
	<td>0.0518556</td>
	<td>0.9386362</td>
	<td>-48.1464047</td>
	<td>17.3295217</td></tr>
	<tr><td></td>
	<td>15</td>
	<td>0.8999962</td>
	<td>0.0801775</td>
	<td>0.3945866</td>
	<td>1.0867750</td>
	<td>0.0719359</td>
	<td>0.1981266</td>
	<td>0.0394572</td>
	<td>0.9780933</td>
	<td>-60.5413434</td>
	<td>8.6774970</td></tr>
	<tr><td></td>
	<td>16</td>
	<td>1.0</td>
	<td>0.0597666</td>
	<td>0.2190584</td>
	<td>1.0</td>
	<td>0.0399359</td>
	<td>0.1823069</td>
	<td>0.0219067</td>
	<td>1.0</td>
	<td>-78.0941597</td>
	<td>0.0</td></tr></table></div>
	</div>

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	<pre><bound method ModelBase.weights of ></pre>
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	<h3 id="Test-Data-Sets-for-Binary-Classifier">Test Data Sets for Binary Classifier<a class="anchor-link" href="#Test-Data-Sets-for-Binary-Classifier">¶</a></h3><h4 id="Some-Kaggle-Binary-classification-competitions">Some Kaggle Binary classification competitions<a class="anchor-link" href="#Some-Kaggle-Binary-classification-competitions">¶</a></h4><p>The idea here is to get a range of datasets to test our H2O binary classification models as well as to understand which approaches work best for binary classification. The hope is to get a single model or set of models that perform well in these competitions as well as logic and tests to dynamically choose the best models and their parameters.</p>
	<p><a href="https://www.kaggle.com/c/santander-customer-satisfaction">Santander Customer Satisfaction</a></p>
	<p><a href="https://www.kaggle.com/c/facebook-recruiting-iv-human-or-bot">Facebook Recruiting IV: Human or Robot?</a></p>
	<p><a href="https://www.kaggle.com/c/donorschoose-application-screening">DonorsChoose.org Application Screening Predict whether teachers' project proposals are accepted</a></p>
	<p><a href="https://www.kaggle.com/c/statoil-iceberg-classifier-challenge">Statoil/C-CORE Iceberg Classifier Challenge Ship or iceberg, can you decide from space?</a></p>
	<p><a href="https://www.kaggle.com/c/kkbox-churn-prediction-challenge">WSDM - KKBox's Churn Prediction Challenge Can you predict when subscribers will churn?</a></p>
	<p><a href="https://www.kaggle.com/c/porto-seguro-safe-driver-prediction">Porto Seguro’s Safe Driver Prediction Predict if a driver will file an insurance claim next year.</a></p>
	<p><a href="https://www.kaggle.com/c/dato-native">Porto Seguro’s Safe Driver Prediction Predict if a driver will file an insurance claim next year.</a></p>
	<p><a href="https://www.kaggle.com/c/data-science-bowl-2017">Data Science Bowl 2017 Can you improve lung cancer detection?</a></p>
	<p><a href="https://www.kaggle.com/c/random-acts-of-pizza">Random Acts of Pizza Predicting altruism through free pizza</a></p>

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	<p>Last update: October 3, 2018</p>

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